CA2471592A1 - Systems, methods and software for hyperlinking names - Google Patents
Systems, methods and software for hyperlinking names Download PDFInfo
- Publication number
- CA2471592A1 CA2471592A1 CA002471592A CA2471592A CA2471592A1 CA 2471592 A1 CA2471592 A1 CA 2471592A1 CA 002471592 A CA002471592 A CA 002471592A CA 2471592 A CA2471592 A CA 2471592A CA 2471592 A1 CA2471592 A1 CA 2471592A1
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- name
- cndot
- names
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- 230000008520 organization Effects 0.000 claims 3
- 230000004044 response Effects 0.000 claims 3
- 230000001502 supplementing effect Effects 0.000 claims 2
- 239000000284 extract Substances 0.000 abstract 1
Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/93—Document management systems
- G06F16/94—Hypermedia
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- 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
- G06F16/3332—Query translation
- G06F16/3338—Query expansion
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/955—Retrieval from the web using information identifiers, e.g. uniform resource locators [URL]
- G06F16/9558—Details of hyperlinks; Management of linked annotations
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- 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
Abstract
Hyperlinking or associating documents to other documents based on the names of people in the documents has become more desirable. Although there is an automated system for installing such hyperlinks into judicial opinions, the system is not generally applicable to other types of names and documents, nor well suited to determine hyperlinks for names that might refer to two or more similarly named persons. Accordingly, the inventor devised systems, methods, and software that facilitate hyperlinking names in documents, regardless of type. One exemplary system includes a descriptor module and a linking module.
The descriptor module develops descriptive patterns for selecting co-occurent document information that is useful in recognizing associations between names and professional classes. The linking module tags names in an input document, extracts co-occurent information using the descriptive patterns, and uses a Bayesian inference network that processes a (non-inverse-document-frequency) name-rarity score for each name along with the name and selected co-occurent document information to determine appropriate hyperlinks to other documents, such as entries in professional directories.
The descriptor module develops descriptive patterns for selecting co-occurent document information that is useful in recognizing associations between names and professional classes. The linking module tags names in an input document, extracts co-occurent information using the descriptive patterns, and uses a Bayesian inference network that processes a (non-inverse-document-frequency) name-rarity score for each name along with the name and selected co-occurent document information to determine appropriate hyperlinks to other documents, such as entries in professional directories.
Claims (39)
1. A computer-implemented method comprising:
.cndot. identifying a name in a document;
.cndot. determining a rarity indicator for the name; and .cndot. defining a hyperlink for the name based on the rarity indicator.
.cndot. identifying a name in a document;
.cndot. determining a rarity indicator for the name; and .cndot. defining a hyperlink for the name based on the rarity indicator.
2. The computer-implemented method of claim 1, wherein the name is a person name.
3. The computer-implemented method of claim 1, wherein the rarity indicator is a quantity based on a probability of drawing at least a portion of the name at random from a set of sample names representative of a relevant human population.
4. The computer-implemented method of claim 1, wherein the rarity indicator is a quantity based on a size of a human population, a probability of drawing a first portion of the name at random, and a probability of drawing a second portion of the name at random.
5. The computer-implemented method of claim 1, wherein the first portion is a first name portion of the name and the second portion is a last name portion of the name.
6. The computer-implemented method of claim 1, wherein defining a hyperlink for the name based on the rarity indicator, comprises:
.cndot. identifying one or more non-person-name terms from the document;
.cndot. identifying one or more candidate records in a database based on at least a portion of the name;
.cndot. comparing the non-person-name terms for each of the candidate records to the non-person-name terms from the document;
.cndot. calculating one or more quantities, each based on the rarity indicator for the person name and the comparison of the non-person-name terms for one of the candidate records; and .cndot. defining the hyperlink based on the one or more calculated quantities.
.cndot. identifying one or more non-person-name terms from the document;
.cndot. identifying one or more candidate records in a database based on at least a portion of the name;
.cndot. comparing the non-person-name terms for each of the candidate records to the non-person-name terms from the document;
.cndot. calculating one or more quantities, each based on the rarity indicator for the person name and the comparison of the non-person-name terms for one of the candidate records; and .cndot. defining the hyperlink based on the one or more calculated quantities.
7. The computer-implemented method of claim 6, wherein calculating one or more quantities, each based on the rarity indicator for the person name and the comparison of the non-person-name terms for one of the candidate records, includes using a Bayesian inference engine.
8. The computer-implemented method of claim 6, wherein defining the hyperlink based on the one or more calculated quantities comprises:
.cndot. comparing the quantities to a threshold; and .cndot. defining the hyperlink based on a greatest one of the quantities exceeding the threshold.
.cndot. comparing the quantities to a threshold; and .cndot. defining the hyperlink based on a greatest one of the quantities exceeding the threshold.
9. The computer-implemented method of claim 8, wherein defining the hyperlink based on the greatest one of the quantities exceeding the threshold comprises defining a hyperlink to designate the candidate record corresponding to the greatest one of the quantities.
10. A machine-readable medium comprising machine executable instructions for performing the computer-implemented method of claim 1.
11. A machine-readable medium comprising machine executable instructions for performing the computer-implemented method of claim 9.
12. A system for adding a hyperlink to a document including a person name, the system comprising:
.cndot. at least one processor;
.cndot. a memory coupled to the processor, the memory including instructions for:
~ identifying a name in a document;
~ determining a rarity indicator for the name; and ~ defining a hyperlink for the name based on the rarity indicator.
.cndot. at least one processor;
.cndot. a memory coupled to the processor, the memory including instructions for:
~ identifying a name in a document;
~ determining a rarity indicator for the name; and ~ defining a hyperlink for the name based on the rarity indicator.
13. The system of claim 12, wherein the name is a person name.
14. The system of claim 12, wherein the rarity indicator is a quantity based on a probability of drawing at least a portion of the name at random from a set of sample names representative of a relevant human population.
15. The system of claim 12, wherein the rarity indicator is a quantity based on a size of a human population, a probability of drawing a first portion of the name at random, and a probability of drawing a second portion of the name at random from a set of sample names representative of a relevant human population.
16. The system of claim 12, wherein defining a hyperlink for the name based on the rarity indicator, comprises:
.cndot. identifying one or more non-person-name terms from the document;
.cndot. identifying one or more candidate records in a database based on at least a portion of the name;
.cndot. comparing the non-person-name terms for each of the candidate records to the non-person-name terms from the document;
.cndot. calculating one or more quantities, each based on the rarity indicator for the person name and the comparison of the non-person-name terms for one of the candidate records; and .cndot. defining the hyperlink based on the one or more calculated quantities.
.cndot. identifying one or more non-person-name terms from the document;
.cndot. identifying one or more candidate records in a database based on at least a portion of the name;
.cndot. comparing the non-person-name terms for each of the candidate records to the non-person-name terms from the document;
.cndot. calculating one or more quantities, each based on the rarity indicator for the person name and the comparison of the non-person-name terms for one of the candidate records; and .cndot. defining the hyperlink based on the one or more calculated quantities.
17. A computer-implemented method comprising:
.cndot. identifying one or more person names in a set of one or more documents, with each identified person name more likely to refer to a single person in a profession than other person names in the document;
.cndot. identifying descriptive language from one or more documents, based on the identified names; and .cndot. identifying within one or more documents other person names that refer to persons in the profession, based on one or more portions of the identified descriptive language.
.cndot. identifying one or more person names in a set of one or more documents, with each identified person name more likely to refer to a single person in a profession than other person names in the document;
.cndot. identifying descriptive language from one or more documents, based on the identified names; and .cndot. identifying within one or more documents other person names that refer to persons in the profession, based on one or more portions of the identified descriptive language.
18. The computer-implemented method of claim 17, wherein identifying person names in a set of documents comprises:
.cndot. identifying a plurality of person names in the set of documents, with each name including at least a last name;
.cndot. calculating for each of the plurality of person names, a quantity based on a probability of drawing its last name at random from a set of last names in a search universe.
.cndot. identifying a plurality of person names in the set of documents, with each name including at least a last name;
.cndot. calculating for each of the plurality of person names, a quantity based on a probability of drawing its last name at random from a set of last names in a search universe.
19. The computer-implemented method of claim 17, wherein calculating for each of the plurality of person names a quantity based on the probability of drawing its last name at random from a set of last names, includes:
.cndot. calculating a quantity based on a size of a human population, a probability of drawing a first portion of the name at random from all the first names in a relevant search universe, and a probability of drawing a second portion of the name at random from all the last names in the search universe.
.cndot. calculating a quantity based on a size of a human population, a probability of drawing a first portion of the name at random from all the first names in a relevant search universe, and a probability of drawing a second portion of the name at random from all the last names in the search universe.
20. The computer-implemented method of claim 17, wherein identifying descriptive language from one or more documents, based on the identified names comprises identifying appositives related to the identified names:
21. The computer-implemented method of claim 17, wherein identifying descriptive language from one or more documents, based on the identified names in the set of documents comprises:
.cndot. identifying a set of terms, including one or more first terms preceding one or more of the identified names and one or more second terms succeeding one or more of the identified names.
.cndot. identifying a set of terms, including one or more first terms preceding one or more of the identified names and one or more second terms succeeding one or more of the identified names.
22. The computer-implemented method of claim 17, wherein the one or more first terms includes one or more parts of speech and one or more of the second terms includes one or more parts of speech.
23. A machine-readable medium comprising machine executable instructions for performing the computer-implemented method of claim 16.
24. A system comprising:
.cndot. at least one processor;
.cndot. a memory coupled to the processor, the memory including instructions for:
.cndot. identifying one or more person names in a set of one or more documents, with each identified person name more likely to refer to a single person in a profession than other person names in the document;
.cndot. identifying descriptive language from one or more documents, based on the identified names; and .cndot. identifying within one or more documents other person names that refer to persons in the profession regardless of their name uniqueness, based on one or more portions of the identified descriptive language.
.cndot. at least one processor;
.cndot. a memory coupled to the processor, the memory including instructions for:
.cndot. identifying one or more person names in a set of one or more documents, with each identified person name more likely to refer to a single person in a profession than other person names in the document;
.cndot. identifying descriptive language from one or more documents, based on the identified names; and .cndot. identifying within one or more documents other person names that refer to persons in the profession regardless of their name uniqueness, based on one or more portions of the identified descriptive language.
25. A data structure comprising .cndot. a name; and .cndot. a name-rarity indicator which indicates how likely the name is to refer to more than one entity in a population.
26. The data structure of claim 25, further comprising:
.cndot. one or more organizations co-existent in a document with the name; and .cndot. one or more locations co-existent in a document with the name;
.cndot. one or more organizations co-existent in a document with the name; and .cndot. one or more locations co-existent in a document with the name;
27. The data structure of claim 2, further including positional information indicating relative position of each organization and each location relative to the name.
28. A computer-implemented method comprising:
.cndot. receiving a search query including a name of an entity;
.cndot. determining a measure of how rare the name is in a population; and .cndot. obtaining additional information to assist in answering the query, in response to the determined measure.
.cndot. receiving a search query including a name of an entity;
.cndot. determining a measure of how rare the name is in a population; and .cndot. obtaining additional information to assist in answering the query, in response to the determined measure.
29. The computer-implemented method of claim 28, wherein obtaining additional information to assist in answering the query in response to the determined measure comprises:
.cndot. comparing the measure to a threshold; and .cndot. requesting additional information if the measure is less than the threshold.
.cndot. comparing the measure to a threshold; and .cndot. requesting additional information if the measure is less than the threshold.
30. The computer-implemented method of claim 28, further comprising:
updating the search query based on the additional information.
updating the search query based on the additional information.
31. The computer-implemented method of claim 28, wherein requesting additional information comprises requesting information is related to a profession, a location, and/or an organization.
32. The computer-implemented method of claim 28, wherein obtaining additional information to assist in answering the query in response to the determined measure comprises:
.cndot. comparing the measure to a threshold; and .cndot. searching one or more databases based on the name;
updating or supplementing the query based on results of searching the one or more databases.
.cndot. comparing the measure to a threshold; and .cndot. searching one or more databases based on the name;
updating or supplementing the query based on results of searching the one or more databases.
33. The computer-implemented method of claim 28, wherein updating or supplementing the query comprises:
.cndot. defining one or more sub-queries, with each sub-query including information about a professional title, organization, or location associated with the name.
.cndot. defining one or more sub-queries, with each sub-query including information about a professional title, organization, or location associated with the name.
34. A computer-implemented method comprising: determining rarity of a name in a population.
35. The computer-implemented method of claim 34, further comprising:
.cndot. associating a hyperlink with the name, with at least a portion of the hyperlink defined based on the determined rarity.
.cndot. associating a hyperlink with the name, with at least a portion of the hyperlink defined based on the determined rarity.
36. The computer-implemented method of claim 34, further comprising:
.cndot. receiving a document including at least one occurrence of the name;
and .cndot. identifying the name in the document before determining its rarity.
.cndot. receiving a document including at least one occurrence of the name;
and .cndot. identifying the name in the document before determining its rarity.
37. The computer-implemented method of claim 34, wherein the name is a person name.
38. A system comprising means for determining rarity of a name in a population.
39. The system of claim 38, further comprising:
.cndot. means for associating a hyperlink with the name, with at least a portion of the hyperlink defined based on the determined rarity.
.cndot. means for associating a hyperlink with the name, with at least a portion of the hyperlink defined based on the determined rarity.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CA2754006A CA2754006C (en) | 2001-12-21 | 2002-12-20 | Systems, methods, and software for hyperlinking names |
Applications Claiming Priority (5)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US34295601P | 2001-12-21 | 2001-12-21 | |
| US60/342,956 | 2001-12-21 | ||
| US10/171,170 US7333966B2 (en) | 2001-12-21 | 2002-06-13 | Systems, methods, and software for hyperlinking names |
| US10/171,170 | 2002-06-13 | ||
| PCT/US2002/041144 WO2003060767A2 (en) | 2001-12-21 | 2002-12-20 | System, method and software for automatic hyperlinking of persons’ names in documents to professional directories |
Related Child Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CA2754006A Division CA2754006C (en) | 2001-12-21 | 2002-12-20 | Systems, methods, and software for hyperlinking names |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CA2471592A1 true CA2471592A1 (en) | 2003-07-24 |
| CA2471592C CA2471592C (en) | 2011-12-13 |
Family
ID=26866803
Family Applications (3)
| Application Number | Title | Priority Date | Filing Date |
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| CA2754006A Expired - Lifetime CA2754006C (en) | 2001-12-21 | 2002-12-20 | Systems, methods, and software for hyperlinking names |
| CA2471592A Expired - Lifetime CA2471592C (en) | 2001-12-21 | 2002-12-20 | Systems, methods and software for hyperlinking names |
| CA2924140A Abandoned CA2924140A1 (en) | 2001-12-21 | 2002-12-20 | Systems, methods and software for hyperlinking names |
Family Applications Before (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CA2754006A Expired - Lifetime CA2754006C (en) | 2001-12-21 | 2002-12-20 | Systems, methods, and software for hyperlinking names |
Family Applications After (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CA2924140A Abandoned CA2924140A1 (en) | 2001-12-21 | 2002-12-20 | Systems, methods and software for hyperlinking names |
Country Status (10)
| Country | Link |
|---|---|
| US (2) | US7333966B2 (en) |
| EP (3) | EP2328101A1 (en) |
| JP (2) | JP4436909B2 (en) |
| CN (1) | CN1623146B (en) |
| AT (1) | ATE530989T1 (en) |
| AU (3) | AU2002364593B2 (en) |
| CA (3) | CA2754006C (en) |
| ES (1) | ES2378653T3 (en) |
| NZ (3) | NZ567455A (en) |
| WO (1) | WO2003060767A2 (en) |
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2002
- 2002-06-13 US US10/171,170 patent/US7333966B2/en active Active
- 2002-12-20 ES ES02799974T patent/ES2378653T3/en not_active Expired - Lifetime
- 2002-12-20 EP EP10012722A patent/EP2328101A1/en not_active Ceased
- 2002-12-20 EP EP02799974A patent/EP1474759B1/en not_active Expired - Lifetime
- 2002-12-20 EP EP10012705A patent/EP2336903A1/en not_active Ceased
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- 2002-12-20 CA CA2754006A patent/CA2754006C/en not_active Expired - Lifetime
- 2002-12-20 CA CA2471592A patent/CA2471592C/en not_active Expired - Lifetime
- 2002-12-20 CN CN02828266.3A patent/CN1623146B/en not_active Expired - Lifetime
- 2002-12-20 AU AU2002364593A patent/AU2002364593B2/en not_active Expired
- 2002-12-20 NZ NZ567455A patent/NZ567455A/en not_active IP Right Cessation
- 2002-12-20 NZ NZ534222A patent/NZ534222A/en not_active IP Right Cessation
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- 2002-12-20 WO PCT/US2002/041144 patent/WO2003060767A2/en active Application Filing
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2007
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| US9002764B2 (en) | 2015-04-07 |
| US20030135826A1 (en) | 2003-07-17 |
| NZ552575A (en) | 2008-06-30 |
| AU2002364593B2 (en) | 2008-10-02 |
| US20080301074A1 (en) | 2008-12-04 |
| NZ534222A (en) | 2007-05-31 |
| JP2009259252A (en) | 2009-11-05 |
| EP2336903A1 (en) | 2011-06-22 |
| CA2754006A1 (en) | 2003-07-24 |
| AU2008212604A1 (en) | 2008-10-02 |
| CA2754006C (en) | 2016-05-31 |
| JP5252725B2 (en) | 2013-07-31 |
| NZ567455A (en) | 2009-06-26 |
| CA2471592C (en) | 2011-12-13 |
| AU2008212267A1 (en) | 2008-10-02 |
| JP4436909B2 (en) | 2010-03-24 |
| CN1623146A (en) | 2005-06-01 |
| ES2378653T3 (en) | 2012-04-16 |
| JP2005539283A (en) | 2005-12-22 |
| US7333966B2 (en) | 2008-02-19 |
| CN1623146B (en) | 2014-04-02 |
| EP2328101A1 (en) | 2011-06-01 |
| CA2924140A1 (en) | 2003-07-24 |
| AU2002364593A1 (en) | 2003-07-30 |
| WO2003060767A2 (en) | 2003-07-24 |
| WO2003060767A3 (en) | 2004-08-26 |
| ATE530989T1 (en) | 2011-11-15 |
| EP1474759A2 (en) | 2004-11-10 |
| EP1474759B1 (en) | 2011-10-26 |
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