WO2000075807A1 - System and method for enhancing e-commerce using natural language interface for searching database - Google Patents

System and method for enhancing e-commerce using natural language interface for searching database Download PDF

Info

Publication number
WO2000075807A1
WO2000075807A1 PCT/IB2000/000464 IB0000464W WO0075807A1 WO 2000075807 A1 WO2000075807 A1 WO 2000075807A1 IB 0000464 W IB0000464 W IB 0000464W WO 0075807 A1 WO0075807 A1 WO 0075807A1
Authority
WO
WIPO (PCT)
Prior art keywords
query
user
natural language
interface
database
Prior art date
Application number
PCT/IB2000/000464
Other languages
French (fr)
Inventor
Jean-Michel Livowsky
Original Assignee
Albert-Inc. S.A.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Albert-Inc. S.A. filed Critical Albert-Inc. S.A.
Priority to CA002376671A priority Critical patent/CA2376671A1/en
Priority to EP00914337A priority patent/EP1185941A1/en
Priority to AU35730/00A priority patent/AU3573000A/en
Publication of WO2000075807A1 publication Critical patent/WO2000075807A1/en

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2452—Query translation
    • G06F16/24522—Translation of natural language queries to structured queries
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33—Querying
    • G06F16/3331—Query processing
    • G06F16/334—Query execution
    • G06F16/3344—Query execution using natural language analysis
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00—Data processing: database and file management or data structures
    • Y10S707/99931—Database or file accessing
    • Y10S707/99932—Access augmentation or optimizing
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00—Data processing: database and file management or data structures
    • Y10S707/99931—Database or file accessing
    • Y10S707/99933—Query processing, i.e. searching
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00—Data processing: database and file management or data structures
    • Y10S707/99931—Database or file accessing
    • Y10S707/99933—Query processing, i.e. searching
    • Y10S707/99935—Query augmenting and refining, e.g. inexact access

Definitions

  • the present invention relates generally to e-commerce, and more particularly to a system and method for enhancing e-commerce using a natural language interface.
  • FIG. 1 illustrates a conventional e- commerce system 100 that a consumer can use to purchase, for example, a book or an airline ticket.
  • the system 100 comprises a user interface 104, a service provider 108, and one or more database 112.
  • a consumer can be linked to the user interface 108 via the Internet or other communication links.
  • the consumer purchases goods and services using the service provider 108.
  • the service provider 108 provides the consumer links to one or more databases 112.
  • the service provider 108 may be a retailer, in which case it may provide links to its own databases 112. Alternately, the service provider may merely provide links to other retailers' databases.
  • the database 112 may be one or more server computers that store a list of goods or services.
  • one of the database 112 may include a list of all car dealers in a particular geographical area.
  • Each record in the database 112 may include, for example, the name of a dealer, an address, makes, models, and prices.
  • the service provider 108 provides the user interface 104 with a web page or a form via which the consumer can access the system 100.
  • the consumer uses the web page or the form to formulate a "query" (or a "search request").
  • the consumer formulates a query using the user interface 104.
  • the consumer may type "Car Dealers in Chicago”.
  • the service provider 108 will search the databases 112 and provide a list of car dealers in Chicago. The list provides links to the auto dealers. Then the consumer may select a dealer from the list, and enter the dealer's own web page. The consumer can view the web page and learn more about the cars offered for sale by the dealer. Finally, the consumer can order a car through the web page. This example illustrates how the consumer can use the system 100 to conduct a commercial transaction.
  • a method for enhancing e-commerce using a natural language interface comprises the steps of accessing a user interface provided by a service provider, entering a query using a natural language interface, the query being formed in a natural language, processing the query by the natural language interface, searching a database using the processed query, retrieving results from the database, and providing the results to the user.
  • a system for enhancing e-commerce on the Internet comprises a user interface for receiving a query in a natural language form, a natural language interface coupled to the user interface for processing the query, a service provider coupled to the user interface for receiving the processed query, and one or more databases coupled to the user interface for storing information about one or more retailers selling goods and services on the Internet, wherein the system searches the databases using the processed query and provides the results to the user through the user interface.
  • FIG. 1 illustrates a conventional e-commerce system.
  • FIG. 2 illustrates a system for enhancing e-commerce using a natural language interface in accordance with one embodiment of the present invention.
  • FIG. 3 is a flow diagram illustrating various steps involved in an e-commerce transaction using the system of FIG. 2.
  • the present invention is directed to a system and method for enhancing e-commerce using a natural language interface.
  • the system includes a user interface, a natural language interface, a service provider and one or more databases.
  • the database holds information regarding goods and services sold by retailers.
  • the database may be a general database engine (including, but not limited to Access, Oracle, Sybase, SQL-Server databases), an internal database, located on a network (including, but not limited to intranet or the Internet).
  • the invention allows consumers to conduct e-commerce using a natural language, rather than conventional search terms.
  • the natural language interface is a computer program code, written in C++, Java or any other well known computing language, and configured to process a query (also referred to as a search request) formed in a natural language.
  • the system analyzes the query and converts it into one or more search words (also referred to as search terms).
  • search words are further converted into a string of bytes, and a database referred to as a target database is searched. If there is a match between the integer bytes and raw data in the target database, the raw data is retrieved from the target database.
  • the raw data is then formatted into a selected format and provided to a user.
  • the raw data may include multimedia content, including video, audio, and data.
  • the raw data can be provided to the user unformatted.
  • FIG. 2 illustrates a system 200 for enhancing e-commerce using a natural language interface in accordance with one embodiment of the present invention.
  • the system 200 comprises a user interface 204, a natural language interface 208, a service provider 212, and one or more databases 216.
  • the user accesses the user interface 204 via the Internet.
  • the service provider 212 provides links to one or more databases 216.
  • the service provider 112 may be a retailer, in which case it provides links to its own database 216. Alternately, the service provider may merely provide links to other retailers' databases.
  • the database 216 may store a list of retailers that sell goods or services.
  • the service provider 212 provides the user interface 204.
  • the user interface 204 may be a web page, a form, etc., via which the user can access the system 200 and conduct a transaction. The user uses the web page (or the form) to formulate a query.
  • the natural language interface 208 is at the core of the invention.
  • the natural language interface 208 is coupled to the user interface.
  • the user can access the natural language interface 208 through the user interface 204.
  • the natural language interface 208 is described in detail in the concurrently filed and commonly assigned application titled "Natural Language Interface for Searching Database", Attorney Docket No. 00186.0003, and is incorporated by reference in its entirety for all purposes.
  • the natural language interface 208 allows the user to formulate a query in a natural language form, rather than in conventional search terms.
  • the natural language interface 208 provides the user with a "user friendly" interface.
  • the natural language interface 208 can process a query even if there is not an exact match between the user formulated search words and the content in the database. Thus, even if the user does not use the "right" word in the query, the natural language interface 208 may still be able to assist the system 200 to find a relevant answer. Referring back to an earlier example, if the user types "Vehicle Dealer in Chicago", the natural language interface, will be able to process the query. This is due to the fact that the natural language interface 208 understands that "vehicle" is a synonym for "car.” Furthermore, the natural language interface 208 is capable of processing misspelled queries or queries having syntax errors. Thus a user who made a spelling or a syntax error in the query may still be able to conduct a transaction.
  • the natural language interface 208 provides user specific or personalized answers. For example, if a butcher, a stockbroker, and a boxer each include the word "pound” in a query, they may not be referring to the same object. Since the word "pound” may have different meaning depending on the context, most systems will not be able to correctly process the query for all three users. In contrast, the natural language interface 208 will be able to assist each of the different users by considering the different contexts.
  • FIG. 3 is a flow diagram 300 of steps involved in an e-commerce transaction using the system 200.
  • the user accesses the user interface 204 provided by the service provider 212.
  • the user enters a query using the natural language interface 208.
  • the natural language interface 208 allows the user to formulate the query in a natural language form.
  • the natural language interface 208 processes the query.
  • the database 216 is searched using the processed query.
  • the service provider 212 retrieves results from the database and provides the results to the user.

Abstract

A system and method for enhancing e-commerce using a natural language interface. The natural language interface allows the user to formulate a query in a natural language form, rather than in conventional search terms. The natural language interface provides the user with a 'user friendly' interface. The natural language interface can process a query even if there is not an exact match between the user formulated search words and the content in the database. Furthermore, the natural language interface is capable of processing misspelled queries or queries having syntax errors. The method for enhancing e-commerce using a natural language interface comprises the steps of accessing a user interface provided by a service provider, entering a query using a natural language interface, the query being formed in a natural language, processing the query by the natural language interface, searching a database using the processed query, retrieving results from the database, and providing the results to the user. The system for enhancing e-commerce on the Internet comprises a user interface for receiving a query in a natural language form, a natural language interface coupled to the user interface for processing the query, a service provider coupled to the user interface for receiving the processed query, and one or more databases coupled to the user interface for storing information, wherein the system searches the databases using the processed query and provides the results to the user through the user interface.

Description

SYSTEM AND METHOD FOR ENHANCING E-COMMERCE USING NATURAL LANGUAGE INTERFACE FOR SEARCHING DATABASE
BACKGROUND OF THE INVENTION
I. Related Applications
This application is related to concurrently filed applications titled, "Natural Language Interface for Searching Database", Attorney Docket No. 00186.0003, commonly assigned, and which is incorporated herein by reference, and "System and Method for Enhancing Online Support Services using Natural Language Interface for Searching Database", Attorney Docket No. 00186.0005, commonly assigned, and which is incorporated herein by reference.
H. Field of the Invention
The present invention relates generally to e-commerce, and more particularly to a system and method for enhancing e-commerce using a natural language interface.
HI. Description of the Related Art
Recently, there has been a rapid growth in commercial activities on the Internet. Today, consumers are frequently relying on the Internet to purchase goods and services. For example, consumers are using the Internet to purchase airline tickets, books, music, etc. This type of transactions is commonly referred to as electronic commerce or "e-commerce."
Many retailers provide e-commerce services on the Internet. These services enable buyers to purchase various goods and services on the Internet. FIG. 1 illustrates a conventional e- commerce system 100 that a consumer can use to purchase, for example, a book or an airline ticket. The system 100 comprises a user interface 104, a service provider 108, and one or more database 112. In the system 100, a consumer can be linked to the user interface 108 via the Internet or other communication links. The consumer purchases goods and services using the service provider 108. The service provider 108 provides the consumer links to one or more databases 112. The service provider 108 may be a retailer, in which case it may provide links to its own databases 112. Alternately, the service provider may merely provide links to other retailers' databases.
The database 112 may be one or more server computers that store a list of goods or services. For example, one of the database 112 may include a list of all car dealers in a particular geographical area. Each record in the database 112 may include, for example, the name of a dealer, an address, makes, models, and prices.
The service provider 108 provides the user interface 104 with a web page or a form via which the consumer can access the system 100. The consumer uses the web page or the form to formulate a "query" (or a "search request"). In operation, the consumer formulates a query using the user interface 104. For example, the consumer may type "Car Dealers in Chicago". In response, the service provider 108 will search the databases 112 and provide a list of car dealers in Chicago. The list provides links to the auto dealers. Then the consumer may select a dealer from the list, and enter the dealer's own web page. The consumer can view the web page and learn more about the cars offered for sale by the dealer. Finally, the consumer can order a car through the web page. This example illustrates how the consumer can use the system 100 to conduct a commercial transaction.
Although, users may conduct transactions using conventional e-commerce systems, there are many disadvantages associated with them. Most systems are not "user friendly." For example, they do not accept queries in a natural language form. Most systems require users to formulate search words with Boolean operators. Thus, users unfamiliar with boolean operators experience difficulties using these search engines.
Also, most systems provide results only if there is an exact match between the user formulated search words and contents in the database. Most systems do not consider synonyms and other approximations of the search words. Thus, if the user does not use the "right" word in the query, it is likely that the search engine will fail to find a relevant answer for the user. Referring back to the above example, if the user types "Vehicle Dealer in Chicago", the system 100 may not be able to process the query. This is due to the fact that the system 100 may not understand that "vehicle" is a synonym for "car."
Furthermore, most systems are not capable of processing misspelled queries or queries having syntax errors. Most systems can not deal with spelling and syntax errors. Thus a user who made a spelling or a syntax error in the query may not be able to find an answer.
Moreover, most systems do not provide user specific or personalized answers. For example, if a butcher, a stockbroker, and a boxer each include the word "pound" in a query, they may not be referring to the same object. Since the word "pound" may have different meaning depending on the context, most systems will not be able to correctly process the query for all three users. Thus, most systems may provide a correct answer to the butcher, but may provide an incorrect answer to the stockbroker and the boxer.
Also, most systems are rigid in that their knowledge database does not evolve through use. Most systems do not extract information from prior search sessions to upgrade its own vocabulary and knowledge database. Also, most systems require an extensive dictionary to operate.
For these reasons, it has been recognized that there is a need for an interface for an e- commerce system that is user friendly and accepts natural language queries. Also, there is a need for an interface that can process misspelled queries and queries having syntax errors. Moreover, there is a need for an interface that allows a system to provide user specific or personalized answers. Furthermore, there is a need for an interface that allows a system to extract information from prior search sessions and upgrade its own vocabulary and knowledge database. SUMMARY OF THE INVENTION
The present invention is directed to a system and method for enhancing e-commerce using a natural language interface. In one embodiment, a method for enhancing e-commerce using a natural language interface comprises the steps of accessing a user interface provided by a service provider, entering a query using a natural language interface, the query being formed in a natural language, processing the query by the natural language interface, searching a database using the processed query, retrieving results from the database, and providing the results to the user.
In one embodiment, a system for enhancing e-commerce on the Internet comprises a user interface for receiving a query in a natural language form, a natural language interface coupled to the user interface for processing the query, a service provider coupled to the user interface for receiving the processed query, and one or more databases coupled to the user interface for storing information about one or more retailers selling goods and services on the Internet, wherein the system searches the databases using the processed query and provides the results to the user through the user interface.
BRIEF DESCRIPTION OF THE DRAWINGS
In the drawings, like reference numbers generally indicate identical, functionally similar, and/or structurally similar elements. The drawings in which an element first appears is indicated by the leftmost digit(s) in the reference number.
FIG. 1 illustrates a conventional e-commerce system.
FIG. 2 illustrates a system for enhancing e-commerce using a natural language interface in accordance with one embodiment of the present invention.
FIG. 3 is a flow diagram illustrating various steps involved in an e-commerce transaction using the system of FIG. 2. DETAILED DESCRIPTION OF THE INVENTION
I. Overview of the Invention
The present invention is directed to a system and method for enhancing e-commerce using a natural language interface. In one embodiment, the system includes a user interface, a natural language interface, a service provider and one or more databases. In one embodiment, the database holds information regarding goods and services sold by retailers. The database may be a general database engine (including, but not limited to Access, Oracle, Sybase, SQL-Server databases), an internal database, located on a network (including, but not limited to intranet or the Internet). The invention allows consumers to conduct e-commerce using a natural language, rather than conventional search terms.
In one embodiment, the natural language interface is a computer program code, written in C++, Java or any other well known computing language, and configured to process a query (also referred to as a search request) formed in a natural language.
Briefly stated, the system analyzes the query and converts it into one or more search words (also referred to as search terms). The search words are further converted into a string of bytes, and a database referred to as a target database is searched. If there is a match between the integer bytes and raw data in the target database, the raw data is retrieved from the target database. The raw data is then formatted into a selected format and provided to a user. The raw data may include multimedia content, including video, audio, and data. Optionally, the raw data can be provided to the user unformatted.
II. Description of the Preferred Embodiments
FIG. 2 illustrates a system 200 for enhancing e-commerce using a natural language interface in accordance with one embodiment of the present invention. The system 200 comprises a user interface 204, a natural language interface 208, a service provider 212, and one or more databases 216.
In one embodiment, the user accesses the user interface 204 via the Internet. The service provider 212 provides links to one or more databases 216. The service provider 112 may be a retailer, in which case it provides links to its own database 216. Alternately, the service provider may merely provide links to other retailers' databases.
The database 216 may store a list of retailers that sell goods or services. In one embodiment, the service provider 212 provides the user interface 204. The user interface 204 may be a web page, a form, etc., via which the user can access the system 200 and conduct a transaction. The user uses the web page (or the form) to formulate a query.
The natural language interface 208 is at the core of the invention. The natural language interface 208 is coupled to the user interface. The user can access the natural language interface 208 through the user interface 204.
The natural language interface 208 is described in detail in the concurrently filed and commonly assigned application titled "Natural Language Interface for Searching Database", Attorney Docket No. 00186.0003, and is incorporated by reference in its entirety for all purposes.
The natural language interface 208 allows the user to formulate a query in a natural language form, rather than in conventional search terms. The natural language interface 208 provides the user with a "user friendly" interface.
Also, the natural language interface 208 can process a query even if there is not an exact match between the user formulated search words and the content in the database. Thus, even if the user does not use the "right" word in the query, the natural language interface 208 may still be able to assist the system 200 to find a relevant answer. Referring back to an earlier example, if the user types "Vehicle Dealer in Chicago", the natural language interface, will be able to process the query. This is due to the fact that the natural language interface 208 understands that "vehicle" is a synonym for "car." Furthermore, the natural language interface 208 is capable of processing misspelled queries or queries having syntax errors. Thus a user who made a spelling or a syntax error in the query may still be able to conduct a transaction.
Moreover, the natural language interface 208 provides user specific or personalized answers. For example, if a butcher, a stockbroker, and a boxer each include the word "pound" in a query, they may not be referring to the same object. Since the word "pound" may have different meaning depending on the context, most systems will not be able to correctly process the query for all three users. In contrast, the natural language interface 208 will be able to assist each of the different users by considering the different contexts.
These features allow the natural language interface 208 to enhance e-commerce. Furthermore, these features allow the natural language interface 208 to enlarge and retain the service provider's customer base.
FIG. 3 is a flow diagram 300 of steps involved in an e-commerce transaction using the system 200. In a step 304, the user accesses the user interface 204 provided by the service provider 212. In a step 308, the user enters a query using the natural language interface 208. The natural language interface 208 allows the user to formulate the query in a natural language form. In a step 312, the natural language interface 208 processes the query. In a step 316, the database 216 is searched using the processed query. In a step 320, the service provider 212 retrieves results from the database and provides the results to the user.

Claims

WHAT IS CLAIMED IS:
1. A method for enhancing e-commerce using a natural language interface, comprising the steps of: accessing a user interface provided by a service provider; entering a query using a natural language interface, the query being formed in a natural language form; processing the query by the natural language interface; searching a database using the processed query; retrieving results from the database; and providing the results to the user.
2. The method as recited in claim 1, further comprising the steps of: generating synonyms of the query by the natural language interface; and searching the database using the synonyms.
3. The method as recited in claim 1, further comprising the steps of: generating phonetic approximations of the query by the natural language interface; and searching the database using the phonetic approximations.
4. The method as recited in claim 1, further comprising the steps of: creating a preference file for the user; storing information about the user in the preference file, the information including information related to the user's identification and information regarding the user's own vocabulary, use of synonyms, common spelling errors, and unique writing style; and retrieving stored information from the preference file to analyze the query.
5. The method as recited in claim 1, further comprising the steps of: extracting essential words from the query and ignoring non-essential words from the query in order to generate a most restrictive query; and generating additional queries from the essential words using synonyms, phonetically similar words, and spelling corrections.
6. The method as recited in claim 4, further comprising the steps of: searching the database using the most restrictive query; and searching the database using the additional queries in a predetermined order.
7. The method as recited in claim 1, further comprising the step of formatting the results from the database into a preselected format.
8. A system for enhancing e-commerce on the Internet, the system allowing a user to purchase goods and services, the user being linked to the system via the Internet, comprising: a user interface for receiving a query in a natural language form; a natural language interface coupled to the user interface for processing the query; a service provider coupled to the user interface for receiving the processed query; and one or more databases coupled to the user interface for storing information, wherein the system searches the databases using the processed query and provides the results to the user through the user interface.
9. The system as recited in claim 8, wherein the user interface is a web page via which the user can access the system to conduct e-commerce.
10. The system as recited in claim 8, further comprising one or more preference files for storing information about the user, including personal information related to the user, and information regarding the user's own vocabulary, use of synonyms, common spelling errors, and unique writing style, wherein the stored information is retrieved from the preference file to analyze the query.
11. The system as recited in claim 8, further comprising: means for generating synonyms of the query by the natural language interface; and means for searching the database using the synonyms.
12. The system as recited in claim 8, further comprising: means for generating phonetic approximations of the query by the natural language interface; and means for searching the database using the phonetic approximations.
13. The system as recited in claim 8, further comprising: means for extracting essential words from the query and ignoring non-essential words from the query in order to generate a most restrictive query; and means for generating additional queries from the essential words using synonyms, phonetically similar words, and spelling corrections.
PCT/IB2000/000464 1999-06-08 2000-04-14 System and method for enhancing e-commerce using natural language interface for searching database WO2000075807A1 (en)

Priority Applications (3)

Application Number Priority Date Filing Date Title
CA002376671A CA2376671A1 (en) 1999-06-08 2000-04-14 System and method for enhancing e-commerce using natural language interface for searching database
EP00914337A EP1185941A1 (en) 1999-06-08 2000-04-14 System and method for enhancing e-commerce using natural language interface for searching database
AU35730/00A AU3573000A (en) 1999-06-08 2000-04-14 System and method for enhancing e-commerce using natural language interface for searching database

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US09/327,604 1999-06-08
US09/327,604 US6446064B1 (en) 1999-06-08 1999-06-08 System and method for enhancing e-commerce using natural language interface for searching database

Publications (1)

Publication Number Publication Date
WO2000075807A1 true WO2000075807A1 (en) 2000-12-14

Family

ID=23277243

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/IB2000/000464 WO2000075807A1 (en) 1999-06-08 2000-04-14 System and method for enhancing e-commerce using natural language interface for searching database

Country Status (5)

Country Link
US (1) US6446064B1 (en)
EP (1) EP1185941A1 (en)
AU (1) AU3573000A (en)
CA (1) CA2376671A1 (en)
WO (1) WO2000075807A1 (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2073161A1 (en) * 2007-01-19 2009-06-24 Huawei Technologies Co Ltd Matching method and system for marketing campaign recommendation
US9953092B2 (en) 2009-08-21 2018-04-24 Mikko Vaananen Method and means for data searching and language translation

Families Citing this family (33)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9076448B2 (en) 1999-11-12 2015-07-07 Nuance Communications, Inc. Distributed real time speech recognition system
US7050977B1 (en) 1999-11-12 2006-05-23 Phoenix Solutions, Inc. Speech-enabled server for internet website and method
US7392185B2 (en) 1999-11-12 2008-06-24 Phoenix Solutions, Inc. Speech based learning/training system using semantic decoding
US7725307B2 (en) 1999-11-12 2010-05-25 Phoenix Solutions, Inc. Query engine for processing voice based queries including semantic decoding
US6760601B1 (en) * 1999-11-29 2004-07-06 Nokia Corporation Apparatus for providing information services to a telecommunication device user
US6687689B1 (en) 2000-06-16 2004-02-03 Nusuara Technologies Sdn. Bhd. System and methods for document retrieval using natural language-based queries
WO2002010981A2 (en) * 2000-07-28 2002-02-07 Easyask, Inc. Distributed search system and method
WO2002021337A1 (en) * 2000-09-06 2002-03-14 Daryl Craig Josephson Data gathering and distribution apparatus and methods
US6775666B1 (en) * 2001-05-29 2004-08-10 Microsoft Corporation Method and system for searching index databases
CN100392644C (en) * 2002-05-28 2008-06-04 弗拉迪米尔·叶夫根尼耶维奇·涅博利辛 Method for synthesising self-learning system for knowledge acquistition for retrieval systems
US7266553B1 (en) * 2002-07-01 2007-09-04 Microsoft Corporation Content data indexing
ATE409332T1 (en) * 2004-06-24 2008-10-15 Nxp Bv METHOD, READER AND SYSTEM FOR LOCATING OBJECTS
US7376645B2 (en) * 2004-11-29 2008-05-20 The Intellection Group, Inc. Multimodal natural language query system and architecture for processing voice and proximity-based queries
US7594217B2 (en) * 2004-12-07 2009-09-22 International Business Machines Corporation Matching client interfaces with service interfaces
US7779430B2 (en) * 2004-12-15 2010-08-17 International Business Machines Corporation Method, system, and article of manufacture for providing service components
US7739656B2 (en) * 2004-12-15 2010-06-15 International Business Machines Corporation Generating asynchronous interfaces and methods from synchronous interfaces and methods
US7873654B2 (en) * 2005-01-24 2011-01-18 The Intellection Group, Inc. Multimodal natural language query system for processing and analyzing voice and proximity-based queries
US8150872B2 (en) * 2005-01-24 2012-04-03 The Intellection Group, Inc. Multimodal natural language query system for processing and analyzing voice and proximity-based queries
US20070073678A1 (en) * 2005-09-23 2007-03-29 Applied Linguistics, Llc Semantic document profiling
US20070073745A1 (en) * 2005-09-23 2007-03-29 Applied Linguistics, Llc Similarity metric for semantic profiling
CN101324887B (en) * 2007-06-11 2011-08-24 国际商业机器公司 Method and apparatus for searching information resource
US20080312939A1 (en) * 2007-06-13 2008-12-18 Mdb Capital Group, Llc Automated Identification of Employment History
US20120317217A1 (en) * 2009-06-22 2012-12-13 United Parents Online Ltd. Methods and systems for managing virtual identities
US20110025519A1 (en) * 2009-07-30 2011-02-03 Intelligent Sustainable Energy Limited Non-intrusive utility monitoring
US8402032B1 (en) 2010-03-25 2013-03-19 Google Inc. Generating context-based spell corrections of entity names
US9069814B2 (en) * 2011-07-27 2015-06-30 Wolfram Alpha Llc Method and system for using natural language to generate widgets
JP5951300B2 (en) * 2012-03-19 2016-07-13 株式会社東芝 Service control apparatus, service control method, and service control program
US9824122B2 (en) 2013-03-15 2017-11-21 Entit Software Llc Requests for source code text
US8898063B1 (en) * 2013-03-15 2014-11-25 Mark Sykes Method for converting speech to text, performing natural language processing on the text output, extracting data values and matching to an electronic ticket form
US20150254750A1 (en) * 2014-03-05 2015-09-10 Intuit Inc. Performing commerce queries using a commerce graph
US20150254702A1 (en) * 2014-03-07 2015-09-10 International Business Machines Corporation Natural language searching with price negotiation
US10932009B2 (en) * 2019-03-08 2021-02-23 Fcb Worldwide, Inc. Technologies for analyzing and searching for features in image data
US11934891B2 (en) 2021-02-18 2024-03-19 International Business Machines Corporation APIA configuration using auto-rationalization and modeling

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4674066A (en) * 1983-02-18 1987-06-16 Houghton Mifflin Company Textual database system using skeletonization and phonetic replacement to retrieve words matching or similar to query words
WO1998025217A1 (en) * 1996-12-04 1998-06-11 Quarterdeck Corporation Method and apparatus for natural language querying and semantic searching of an information database
WO1998049640A1 (en) * 1997-04-29 1998-11-05 Mci Worldcom, Inc. Client profile management within a marketing system
WO2000003329A1 (en) * 1998-07-02 2000-01-20 Activepoint Ltd. Virtual sales representative

Family Cites Families (42)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4974191A (en) 1987-07-31 1990-11-27 Syntellect Software Inc. Adaptive natural language computer interface system
US5218536A (en) 1988-05-25 1993-06-08 Franklin Electronic Publishers, Incorporated Electronic spelling machine having ordered candidate words
SE466029B (en) 1989-03-06 1991-12-02 Ibm Svenska Ab DEVICE AND PROCEDURE FOR ANALYSIS OF NATURAL LANGUAGES IN A COMPUTER-BASED INFORMATION PROCESSING SYSTEM
US5197005A (en) 1989-05-01 1993-03-23 Intelligent Business Systems Database retrieval system having a natural language interface
EP0408812B1 (en) 1989-07-21 2000-03-01 Hewlett-Packard Company Distributed object based systems
US5257366A (en) 1990-03-27 1993-10-26 International Business Machines Corporation Query language execution on heterogeneous database servers using a bind-file bridge between application and database languages
US5317742A (en) 1991-06-21 1994-05-31 Racal-Datacom, Inc. Dynamic translation of network management primitives to queries to a database
US5428772A (en) 1991-10-01 1995-06-27 Prime Computer, Inc. Data processing system providing user interaction in multiple natural languages
US5265065A (en) 1991-10-08 1993-11-23 West Publishing Company Method and apparatus for information retrieval from a database by replacing domain specific stemmed phases in a natural language to create a search query
US5404507A (en) 1992-03-02 1995-04-04 At&T Corp. Apparatus and method for finding records in a database by formulating a query using equivalent terms which correspond to terms in the input query
US5377103A (en) * 1992-05-15 1994-12-27 International Business Machines Corporation Constrained natural language interface for a computer that employs a browse function
JPH05324713A (en) * 1992-05-20 1993-12-07 Hitachi Ltd Method and system for natural language processing
US5454106A (en) * 1993-05-17 1995-09-26 International Business Machines Corporation Database retrieval system using natural language for presenting understood components of an ambiguous query on a user interface
US5519608A (en) 1993-06-24 1996-05-21 Xerox Corporation Method for extracting from a text corpus answers to questions stated in natural language by using linguistic analysis and hypothesis generation
US5495604A (en) 1993-08-25 1996-02-27 Asymetrix Corporation Method and apparatus for the modeling and query of database structures using natural language-like constructs
JP3067966B2 (en) 1993-12-06 2000-07-24 松下電器産業株式会社 Apparatus and method for retrieving image parts
US5590319A (en) 1993-12-15 1996-12-31 Information Builders, Inc. Query processor for parallel processing in homogenous and heterogenous databases
US6381595B1 (en) 1994-09-29 2002-04-30 International Business Machines Corporation System and method for compensation of functional differences between heterogeneous database management systems
US5768577A (en) 1994-09-29 1998-06-16 International Business Machines Corporation Performance optimization in a heterogeneous, distributed database environment
US5694593A (en) 1994-10-05 1997-12-02 Northeastern University Distributed computer database system and method
US5491820A (en) 1994-11-10 1996-02-13 At&T Corporation Distributed, intermittently connected, object-oriented database and management system
US5740421A (en) 1995-04-03 1998-04-14 Dtl Data Technologies Ltd. Associative search method for heterogeneous databases with an integration mechanism configured to combine schema-free data models such as a hyperbase
US5710918A (en) 1995-06-07 1998-01-20 International Business Machines Corporation Method for distributed task fulfillment of web browser requests
US5754841A (en) 1995-10-20 1998-05-19 Ncr Corporation Method and apparatus for parallel execution of user-defined functions in an object-relational database management system
US5787424A (en) 1995-11-30 1998-07-28 Electronic Data Systems Corporation Process and system for recursive document retrieval
US5787410A (en) 1996-02-20 1998-07-28 Oracle Corporation Method and apparatus for storing and retrieving data in multiple languages simultaneously using a fully-populated sub-table
US5878219A (en) 1996-03-12 1999-03-02 America Online, Inc. System for integrating access to proprietary and internet resources
US5752028A (en) 1996-04-03 1998-05-12 Ellacott; Bruce Arthur Object-oriented query mechanism
US5778368A (en) 1996-05-03 1998-07-07 Telogy Networks, Inc. Real-time embedded software respository with attribute searching apparatus and method
US5765028A (en) 1996-05-07 1998-06-09 Ncr Corporation Method and apparatus for providing neural intelligence to a mail query agent in an online analytical processing system
US5826261A (en) 1996-05-10 1998-10-20 Spencer; Graham System and method for querying multiple, distributed databases by selective sharing of local relative significance information for terms related to the query
US5864845A (en) 1996-06-28 1999-01-26 Siemens Corporate Research, Inc. Facilitating world wide web searches utilizing a multiple search engine query clustering fusion strategy
US5864846A (en) 1996-06-28 1999-01-26 Siemens Corporate Research, Inc. Method for facilitating world wide web searches utilizing a document distribution fusion strategy
US5768589A (en) 1996-07-12 1998-06-16 Oracle Corporation Method and apparatus for executing stored procedures in a foreign database management system
US5809502A (en) 1996-08-09 1998-09-15 Digital Equipment Corporation Object-oriented interface for an index
US5873080A (en) 1996-09-20 1999-02-16 International Business Machines Corporation Using multiple search engines to search multimedia data
US5836771A (en) 1996-12-02 1998-11-17 Ho; Chi Fai Learning method and system based on questioning
US6078914A (en) 1996-12-09 2000-06-20 Open Text Corporation Natural language meta-search system and method
US5956711A (en) * 1997-01-16 1999-09-21 Walter J. Sullivan, III Database system with restricted keyword list and bi-directional keyword translation
JPH1145266A (en) 1997-07-28 1999-02-16 Just Syst Corp Document retrieval device and computer readable recording medium recorded with program for functioning computer as the device
US5895466A (en) * 1997-08-19 1999-04-20 At&T Corp Automated natural language understanding customer service system
US6144958A (en) * 1998-07-15 2000-11-07 Amazon.Com, Inc. System and method for correcting spelling errors in search queries

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4674066A (en) * 1983-02-18 1987-06-16 Houghton Mifflin Company Textual database system using skeletonization and phonetic replacement to retrieve words matching or similar to query words
WO1998025217A1 (en) * 1996-12-04 1998-06-11 Quarterdeck Corporation Method and apparatus for natural language querying and semantic searching of an information database
WO1998049640A1 (en) * 1997-04-29 1998-11-05 Mci Worldcom, Inc. Client profile management within a marketing system
WO2000003329A1 (en) * 1998-07-02 2000-01-20 Activepoint Ltd. Virtual sales representative

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
JULIAN LAURI; KNIGHTLY JOHN: "Brightware Ships Web's First Automated Real-time Advice Agent", PRESSRELEASE, 29 June 1998 (1998-06-29), XP002924861, Retrieved from the Internet <URL:http://www.brightware.com/news/98_6_29_bwships.html> [retrieved on 20000824] *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2073161A1 (en) * 2007-01-19 2009-06-24 Huawei Technologies Co Ltd Matching method and system for marketing campaign recommendation
EP2073161A4 (en) * 2007-01-19 2010-01-20 Huawei Tech Co Ltd Matching method and system for marketing campaign recommendation
US9953092B2 (en) 2009-08-21 2018-04-24 Mikko Vaananen Method and means for data searching and language translation

Also Published As

Publication number Publication date
AU3573000A (en) 2000-12-28
CA2376671A1 (en) 2000-12-14
US6446064B1 (en) 2002-09-03
EP1185941A1 (en) 2002-03-13

Similar Documents

Publication Publication Date Title
US6446064B1 (en) System and method for enhancing e-commerce using natural language interface for searching database
US7412442B1 (en) Augmenting search query results with behaviorally related items
US7395259B2 (en) Search engine system and associated content analysis methods for locating web pages with product offerings
US10032207B2 (en) Product placement engine and method
US6963867B2 (en) Search query processing to provide category-ranked presentation of search results
US8364661B2 (en) System and method for providing a response to a search query
JP4035685B2 (en) System and method for correcting spelling errors in search queries
US6850934B2 (en) Adaptive search engine query
US7788134B1 (en) Method and system for displaying items using geographic attributes
US7672951B1 (en) Guided navigation system
US20070118514A1 (en) Command Engine
US20100235311A1 (en) Question and answer search
US9342503B1 (en) Correlation across languages
US20120023391A1 (en) Providing useful information associated with an item in a document
EP1240605A1 (en) System and method for locating and displaying web-based product offerings
EP1185943A1 (en) System and method for enhancing online support services using natural language interface for searching database
KR20120082449A (en) Dynamic search suggestion and category specific completion
US10026112B2 (en) Systems and methods for storing and retrieving goods and services information using parameter/value databases
US20090089261A1 (en) Method for resolving failed search queries
US20020129026A1 (en) Process for accessing information via a communications network
US7457802B2 (en) Internet searching enhancement method for determining topical relevance scores
US7062482B1 (en) Techniques for phonetic searching
US20090157631A1 (en) Database search enhancements
US20060178889A1 (en) Method and system for performing electronic commerce
GB2460045A (en) Analysing multiple data sources for a user request using business and geographical data, with selected rule sets to filter the data on the databases.

Legal Events

Date Code Title Description
AK Designated states

Kind code of ref document: A1

Designated state(s): AE AG AL AM AT AU AZ BA BB BG BR BY CA CH CN CR CU CZ DE DK DM DZ EE ES FI GB GD GE GH GM HR HU ID IL IN IS JP KE KG KP KR KZ LC LK LR LS LT LU LV MA MD MG MK MN MW MX NO NZ PL PT RO RU SD SE SG SI SK SL TJ TM TR TT TZ UA UG UZ VN YU ZA ZW

AL Designated countries for regional patents

Kind code of ref document: A1

Designated state(s): GH GM KE LS MW SD SL SZ TZ UG ZW AM AZ BY KG KZ MD RU TJ TM AT BE CH CY DE DK ES FI FR GB GR IE IT LU MC NL PT SE BF BJ CF CG CI CM GA GN GW ML MR NE SN TD TG

121 Ep: the epo has been informed by wipo that ep was designated in this application
DFPE Request for preliminary examination filed prior to expiration of 19th month from priority date (pct application filed before 20040101)
ENP Entry into the national phase

Ref document number: 2376671

Country of ref document: CA

Ref country code: CA

Ref document number: 2376671

Kind code of ref document: A

Format of ref document f/p: F

WWE Wipo information: entry into national phase

Ref document number: 2000914337

Country of ref document: EP

WWP Wipo information: published in national office

Ref document number: 2000914337

Country of ref document: EP

REG Reference to national code

Ref country code: DE

Ref legal event code: 8642

NENP Non-entry into the national phase

Ref country code: JP

WWW Wipo information: withdrawn in national office

Ref document number: 2000914337

Country of ref document: EP