Information retrieval systems with database-selection aids

• US 10,650,058 B2
• Filed: 03/17/2017
• Issued: 05/12/2020
• Est. Priority Date: 12/23/2002
• Status: Active Grant

• Current Assignee: Thomson Reuters Enterprise Centre GmbH (The Woodbridge Co. Ltd.)
• Original Assignee: Thomson Reuters Enterprise Centre GmbH (The Woodbridge Co. Ltd.)
• Inventors: Conrad, Jack G., Claussen, Joanne R. S.
• Primary Examiner(s): Wilson, Kimberly L
• Assistant Examiner(s): Khakhar, Nirav K
• Application Number:
  US15/461,907
• Publication Number:
  US 20170192969A1
• Time in Patent Office: 1,152 Days
• Field of Search: 707754
• CPC Class Codes: G06F 16/245 Query processing
• CPC Class Codes: G06F 16/2457 with adaptation to user needs
• CPC Class Codes: G06F 16/24575 using context
• CPC Class Codes: G06F 16/93 Document management systems
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques

Abstract

A method for enabling a user to search database profiles includes receiving user input categorizing an information need, and determining whether the user input corresponds to a first or a second type of category. In response to determining that the user input corresponds to the first category type, the method includes requesting user input defining a first query, and in response to receipt of the query, and executing the defined first query against a set of one or more databases based on the user input categorizing the information need. In response to determining that the user input corresponds to the second category type, the method includes requesting additional user input regarding the information need.

Claims

1. A method comprising:

receiving a query at a server, said query directed to discovering one or more databases of a plurality of databases which will provide relevant search results from a search of documents stored on the respective one or more databases, wherein the query includes one or more query terms;

searching a set of sample-based database profiles based on the query, with each profile associated with a respective database of the plurality of databases and defined as a document representing terms or phrases and their corresponding frequencies; and

ranking relevance of two or more of the sample-based database profiles, wherein ranking relevance includes determining a relevance score for one or more of the database profiles based on frequency of one or more of the query terms within the database profile and based on frequency of the one or more of the query terms across the set of database profiles.

2. The method of claim 1, wherein ranking relevance further includes:

determining whether the query contains any jurisdictionally relevant terms; and

in response to determining that the query contains no jurisdictionally relevant terms, down-weighting each database profile associated with a jurisdictionally biased database relative to ranking of other database profiles that are not jurisdictionally biased.

3. The method of claim 2, further comprising:

identifying a set of N databases based on results of ranking relevance of the two or more database profiles, with N being a whole number; and

searching one or more of the N databases.

4. The method of claim 2 further comprising:

ranking the one or more databases based on a query;

outputting a list of N ranked databases of the one or more databases, after ranking the one or more databases, wherein each of the N databases has a preceding or succeeding database in the list, and each is associated with a relevance score that has a predetermined relationship with a relevance score associated with the preceding or succeeding database.

5. A method comprising:

receiving a query including a plurality of terms at a server, said query directed to discovering one or more databases of a plurality of databases which will provide relevant search results from a search of documents stored on the respective one or more databases;

identifying one or more terms of the query as belonging to one or more term categories; and

determining search results based on the query, with at least one search result associated with a relevance score based on the identification of at least one of the terms,

wherein identifying one or more of the terms includes determining that one or more of the terms is related to a location or a legal-practice area; and

wherein determining search results based on the query includes computing a term-frequency-and-inverse-document-frequency-based score for the one term and up-weighting the computed score in response to the determination that the one term is related to a location or a legal practice area.

6. The method of claim 5:

wherein identifying one or more of the terms includes determining that one or more of the terms is a generic legal term; and

wherein determining search results based on the query includes computing an inverse-document-frequency-based score for the one term and down-weighting the computed score in response to the determination that it is related to a generic legal concept.

7. The method of claim 6, wherein determining that one or more of the terms is a generic legal term includes determining whether the term is “

law,”

“

regulation,”

“

code,”

“

department,”

“

cases,”

“

reporter,”

or “

journal”

.

8. The method of claim 6, wherein determining whether a term is a generic legal term includes determining utility of the term as a discriminator of one document from another similar document or one database from another database.

9. The method of claim 5 wherein determining search results based on the query includes:

determining whether the query includes jurisdictionally specific content; and

if the determination is that the query does not include jurisdictionally specific content, down-weighting the determined relevance of each database that is jurisdictionally biased relative to other found databases that are not jurisdictionally biased.

10. The method of claim 9, further comprising:

determining whether to automatically execute the received query against one or more of the identified databases.

11. A method comprising:

receiving a query at a server;

in response to receiving the query, identifying a plurality of documents relevant to the query, where each of the documents profiles a corresponding database, with at least one of the documents having a plurality of portions; and

determining a relevance score for each identified document, wherein determining the relevance score for each of the documents having a plurality of portions includes;

determining a plurality of portion relevance scores, with each portion relevance score quantifying relevance of a respective one of the portions to the received query; and

determining the relevance score for the document based on one of the plurality of portion relevance scores, with the one of the plurality of portion relevance scores associated with a most relevant one of the portions of the document.

12. The method of claim 11, wherein the query includes one or more terms, and each portion relevance score is based on an inverse document frequency of one or more of the terms.

13. The method of claim 11, wherein one or more of the portions is delineated by mark-up language tags.

14. The method of claim 11 wherein determining the relevance score for each of the documents having a plurality of portions includes:

determining at least first and second relevance scores for a document, with the first relevance score representing relevance of a first portion of the document to a query, the second relevance score representing relevance of a second portion of the document to the query; and

determining a relevance score for the document, with the relevance score determination substantially excluding one of the first and second relevance scores.

15. The method of claim 14, wherein the relevance score determination for the document completely excludes the one of the first and second scores.

16. The method of claim 14, wherein one or more of the portions is delineated by mark-up language tags.

17. The method of claim 14, wherein each of the documents profiles a corresponding database.