WO2000014651A1 - Document semantic analysis/selection with knowledge creativity capability - Google Patents
Document semantic analysis/selection with knowledge creativity capabilityInfo
- Publication number
- WO2000014651A1 WO2000014651A1 PCT/US1999/019699 US9919699W WO0014651A1 WO 2000014651 A1 WO2000014651 A1 WO 2000014651A1 US 9919699 W US9919699 W US 9919699W WO 0014651 A1 WO0014651 A1 WO 0014651A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- sao
- request
- candidate document
- structures
- extractions
- Prior art date
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/279—Recognition of textual entities
- G06F40/284—Lexical analysis, e.g. tokenisation or collocates
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/205—Parsing
- G06F40/221—Parsing markup language streams
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/30—Semantic analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/30—Semantic analysis
- G06F40/35—Discourse or dialogue representation
-
- 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
- Y10S707/99934—Query formulation, input preparation, or translation
Definitions
- TITLE DOCUMENT SEMANTIC ANALYSIS/SELECTION WITH KNOWLEDGE CREATIVITY CAPABILITY
- the present invention relates to computer based apparatus for and methods of semantically analyzing, selecting, and summarizing candidate documents containing
- Computer based document search processors are known to perform key word searches for publications on the Internet and World Wide Web.
- KD, Inc. of Hong Kong has developed a system that takes into consideration words similar by sense while searching the Web. Today the user can download 10,000 papers from the Web by typing the word "Screen”. The search
- Software based search processors are able to remember requests of single user and
- Web i.e. available in electronic format.
- present invention solves the foregoing problems and has the ability to perform a non-stop search of all databases on the Web or other network for key words and to semantically
- Another aspect of the present invention includes using the semantic analysis results of the selected documents to create new ideas of knowledge concepts.
- the system includes using the semantic analysis results of the selected documents to create new ideas of knowledge concepts.
- the method and apparatus begins
- the system analyzes this request text
- example includes determining and storing the verb groups within the first sentence of the
- the system parses each request sentence with an heirarcal algorithm into a coded framework which is substantially indicative of the sense of the sentence.
- system includes databases of various types to aid in generating the coded framework, such
- a sentence can have one, two, or a plurality of SAO extractions as seen in the detailed description below. Each extraction is normalized into a SAO structure by processing extractions according to certain rules described below.
- the result of the semantic analysis routine performed on the request text is a
- suitable search engine e.g. Alta Vista
- Alta Vista can be used to identify, select, and download candidate documents based on the generated key words.
- the system performs substantially the same semantic analysis on each
- the SAO structures for each sentence for each retrieved document are stored in the system according to the present invention. According to the
- the system analyzes all these stored
- Some of these new structured or strings may be unique and comprise new solutions to problems related to the user's requested subject matter.
- the system stores an association between SI and A2 it can generate S1-A1/A2-O1 to
- Figure 1 is a pictorial representation of one exemplary embodiment of the system
- Figure 2 is a schematic representation of the main architectural elements of the
- Figure 3 is a schematic representation of the method according to the principles of the present invention.
- Figure 4 is a schematic representation of Unit 16 of Figure 2.
- Figure 5 is a schematic representation of Unit 20 of Figure 2.
- Figure 6 is a schematic representation of Unit 22 of Figure 2.
- Figure 7 is a typical example of the user request text entered by user.
- Figure 8 is a tagged and coded representation version of text of Figure 7.
- Figure 9 is an identification of verb groups of the text of Figure 8.
- Figure 10 is an identification of noun groups of the coded text of Figure 8.
- Figure 11 is a representation of parsed hierarchy coded text of Figure 8.
- Figure 12 is a representation of SAO extraction of the text of Figure 7.
- Figure 13 is a representation of SAO structures of the extraction of Figure 12.
- a CPU 12 that could comprise a general purpose personal computer or networked
- System 10 also includes standard
- the semantic procession system 10 includes a temporary storage or data base 12 for receiving and storing documents downloaded from a source.
- semantic processor 14 for receiving the entire text of each document and
- Unit 16 then identifies a code type (such as Markov chain theory code).
- SAO processor Unit 20 applies its output to DB of SAO structures 18.
- SAO processor Unit 20 stores the
- Unit 20 compares the document SAO's to the request SAO's
- Unit 20 documents are stored back in Unit 18 or some other storage facility.
- Unit 20 documents are stored back in Unit 18 or some other storage facility.
- Unit 14 further includes natural language Unit 22 that receives SAO structures in
- Unit 14 also includes keyword Unit 24 for receiving SAO structures and extracts
- Database Units 26, 28, and 30 receive the outputs from Unit 14, generally as
- Unit 16 includes document pre-formatter 32 that receives full text of documents
- Unit 12 converts the text and other contents to a standard plain text format.
- Text coder 34 analyzes each word of each sentence of text and tags a code to every word
- recognizer Unit 36 identifies the verb groups (Fig 9) and the noun groups of each sentence (Fig 10).
- Sentence parser 38 then parses each sentence into a hierarchical coded form that
- S-A-O extractor 40 organizes the SAO's of
- SAO processor 20 includes three main Units. Comparative Unit 46 receives SAO
- Unit 46 compares all candidate documents in sequence and in the same way as described.
- Unit 20 also includes the SAO structure reorganizing Unit 48 to synthesize new
- Filtering Unit 50 analyzes every SAO structure of each document and blocks or
- Reference 52 designates some of the data bases available to aid sub-units of Unit 20.
- SAO synthesizer Unit 22 ( Figure 6) includes a Subject detector 54 for detecting the
- Synthesizer 58 does the same for subject noun groups and synthesizer 60 does the same
- Combiner 68 then organizes and combines these groups into a
- Synthesizer 64 processes the object noun
- units 68, 70 apply output to Unit 26. See Fig 3.
- a session begins with the user inputting a national
- SAO structures These users request SAO structures are stored and applied in two following steps (i) synthesis of key word/phrases
- the request SAO structure key words/phrases are stored and sent to a standard search engine to search for candidate documents in local databases, LANs and/or the
- document text is permanently stored (although it can later be deleted by user if desired)
- Next System 10 filters out the least relevant SAO structures and uses the matched
- SAO structures are processed to reorganize them into new SAO structures for storage
- the new sentences may and probably some of them will express or summarize new ideas, concepts and thoughts for
- the new sentences are stored for user display or print-out.
- the present invention has utility for historians, philosophers, theology,
Abstract
Description
Claims
Priority Applications (5)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CA002341583A CA2341583A1 (en) | 1998-09-09 | 1999-08-31 | Document semantic analysis/selection with knowledge creativity capability |
JP2000569327A JP4467184B2 (en) | 1998-09-09 | 1999-08-31 | Semantic analysis and selection of documents with knowledge creation potential |
AU57903/99A AU5790399A (en) | 1998-09-09 | 1999-08-31 | Document semantic analysis/selection with knowledge creativity capability |
EP99945272A EP1112541A1 (en) | 1998-09-09 | 1999-08-31 | Document semantic analysis/selection with knowledge creativity capability |
NO20011194A NO20011194L (en) | 1998-09-09 | 2001-03-08 | Document semantics analysis / selection with knowledge creativity opportunity |
Applications Claiming Priority (4)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US9964198P | 1998-09-09 | 1998-09-09 | |
US60/099,641 | 1998-09-09 | ||
US09/321,804 US6167370A (en) | 1998-09-09 | 1999-05-27 | Document semantic analysis/selection with knowledge creativity capability utilizing subject-action-object (SAO) structures |
US09/321,804 | 1999-05-27 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2000014651A1 true WO2000014651A1 (en) | 2000-03-16 |
Family
ID=26796312
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/US1999/019699 WO2000014651A1 (en) | 1998-09-09 | 1999-08-31 | Document semantic analysis/selection with knowledge creativity capability |
Country Status (9)
Country | Link |
---|---|
US (2) | US6167370A (en) |
EP (1) | EP1112541A1 (en) |
JP (1) | JP4467184B2 (en) |
KR (1) | KR100594512B1 (en) |
CN (1) | CN1325513A (en) |
AU (1) | AU5790399A (en) |
CA (1) | CA2341583A1 (en) |
NO (1) | NO20011194L (en) |
WO (1) | WO2000014651A1 (en) |
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US20010014852A1 (en) | 2001-08-16 |
CA2341583A1 (en) | 2000-03-16 |
NO20011194L (en) | 2001-05-03 |
US6167370A (en) | 2000-12-26 |
CN1325513A (en) | 2001-12-05 |
JP4467184B2 (en) | 2010-05-26 |
NO20011194D0 (en) | 2001-03-08 |
KR20010075026A (en) | 2001-08-09 |
AU5790399A (en) | 2000-03-27 |
JP2002524799A (en) | 2002-08-06 |
KR100594512B1 (en) | 2006-06-30 |
EP1112541A1 (en) | 2001-07-04 |
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