Search systems and methods with integration of user annotations

• US 9,489,463 B2
• Filed: 05/10/2011
• Issued: 11/08/2016
• Est. Priority Date: 03/15/2004
• Status: Active Grant

• Current Assignee: R2 Solutions LLC (Acacia Research Corporation)
• Original Assignee: Excalibur IP, LLC (Acacia Research Corporation)
• Inventors: Walther, Eckart, Lu, Qi, Ku, David, Lee, Kevin, Tam, Chung-Man, Diab, Ali
• Primary Examiner(s): Willoughby, Alicia
• Application Number:
  US13/104,569
• Publication Number:
  US 20110213805A1
• Time in Patent Office: 2,009 Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/338 Presentation of query results
• CPC Class Codes: G06F 16/8365 Query optimisation
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9538 Presentation of query results
• CPC Class Codes: G06F 16/9558 Details of hyperlinks; Management of linked annotations
• CPC Class Codes: Y10S 707/99942 Manipulating data structure, e.g. compression, compaction, compilation
• CPC Class Codes: Y10S 707/99943 Generating database or data structure, e.g. via user interface
• CPC Class Codes: Y10S 707/99944 Object-oriented database structure
• CPC Class Codes: Y10S 707/99945 Object-oriented database structure processing

Abstract

Computer systems and methods allow users to annotate content items found in a corpus such as the World Wide Web. Annotations, which can include any descriptive and/or evaluative metadata related to a document, are collected from a user and stored in association with that user. Users are able to annotate and view their annotations for any document they encounter while interacting with the corpus, including hits returned in a search of the corpus. Users are also able to search their annotations or to limit searches to documents they have annotated. Metadata from annotations can also be aggregated across users and aggregated metadata applied in generating search results.

Claims

1. A method for responding to a user query, the method being implemented on a machine having at least one processor, storage, and a communication platform, the method comprising:

receiving a query submitted by a user;

identifying a set of documents that are related to the query;

determining ratings associated with individual documents of the set of documents, wherein each of the ratings is either provided by the user or is an inferred rating for the associated document with respect to the user;

determining, for each of the ratings associated with a particular document from the set of documents, a weight based on whether the rating (i) is provided by the user or (ii) is an inferred rating, wherein a weight for an inferred rating is determined based on a number of documents for which the user provided ratings in a category to which the particular document belongs and consistency of the ratings;

determining an additional category related to one other document associated with one other inferred rating of the ratings, wherein determining a weight for each of the ratings further comprises determining a weight for the one other inferred rating based on how many documents for which the user provided a rating that are related to the additional category such that the weight for the one other inferred rating is greater than the weight for the one inferred rating based on the number of documents for which the user provided a rating that are related to the additional category being greater than the number of documents for which the user provided a rating that are related to the category;

computing for the particular document a weighted rating based on the weight associated with the rating;

ranking the set of documents based on weighted ratings of the set of documents; and

generating, based on the ranking, a search report that indicates (i) at least some documents of the set of documents and (ii) at least one of the ratings.

2. The method of claim 1, wherein the set of documents include a first document for which the user provided a first rating and a second document for which the user has not yet provided a rating, the method further comprising:

determining an average of two or more ratings associated with one or more user-rated documents that are similar to the second document;

determining a second rating for the second document based on the average of the two or more ratings, wherein the second rating is an inferred rating determined with respect to the user;

determining a first weight for the first rating based on the first rating being provided by the user as opposed to being an inferred rating determined with respect to the user;

determining a second weight for the second rating based on the second rating being an inferred rating determined with respect to the user as opposed to being provided by the user, wherein the second weight is different than the first weight;

determining a first weighted rating for the first document based on the first rating and the first weight; and

determining a second weighted rating for the second document based on the second rating and the second weight,

wherein ranking the set of documents comprises ranking the set of documents based on the first weighted rating and the second weighted rating.

3. The method of claim 1, wherein determining the respective weights for each of the ratings comprises determining a weight for one inferred rating of the ratings based on one or more degrees of similarity between (i) a document associated with the one inferred rating and (ii) one or more other documents associated with one or more other ratings on which the one inferred rating is based.

4. The method of claim 1, wherein determining the respective weights for each of the ratings comprises determining a weight for one inferred rating of the ratings based on one or more degrees of similarity between (i) a document associated with the one inferred rating and (ii) one or more other documents for which the user has provided a rating on which the one inferred rating is based.

5. The method of claim 1, wherein the query includes a first metadata field specified by the user, and wherein determining the set of documents that are related to the query comprises selecting at least one document for inclusion in the set of documents based on a determination that a metadata field of the at least one document that corresponds to the first metadata field includes information relating to the query.

6. The method of claim 5, wherein the query includes at least one search term specified by the user for the first metadata field, and wherein selecting the at least one document comprises selecting the at least one document for inclusion in the set of documents based on a determination that a metadata field of the at least one document that corresponds to the first metadata field includes information relating to the at least one search term.

7. A computer system for responding to user queries, the system comprising:

at least one processor programmed to execute one or more computer program instructions which, when executed, cause the at least one processor to;

receive a query submitted by a user;

identify a set of documents that are related to the query;

determine ratings associated with individual documents of the set of documents, wherein each of the ratings is either provided by the user or is an inferred rating for the associated document with respect to the user;

determine, for each of the ratings associated with a particular document from the set of documents, a weight based on whether the rating (i) is provided by the user or (ii) is an inferred rating, wherein a weight for an inferred rating is determined based on a number of documents for which the user provided ratings in a category to which the particular document belongs and consistency of the ratings;

determine an additional category related to one other document associated with one other inferred rating of the ratings, wherein determining a weight for each of the ratings comprises determining a weight for the one other inferred rating based on how many documents for which the user provided a rating that are related to the additional category such that the weight for the one other inferred rating is greater than the weight for the one inferred rating based on the number of documents for which the user provided a rating that are related to the additional category being greater than the number of documents for which the user provided a rating that are related to the category;

compute, for the particular document a weighted rating based on the weight associated with the rating;

rank the set of documents based on the weighted ratings of the set of documents; and

generate, based on the ranking, a search report that indicates (i) at least some of the documents of the set of documents and (ii) at least one of the ratings.

8. The system of claim 7, wherein the set of documents include a first document for which the user provided a first rating and a second document for which the user has not yet provided a rating, and wherein the at least one processor is further caused to:

determine an average of two or more ratings associated with one or more user-rated documents that are similar to the second document;

determine a second rating for the second document based on the average of the two or more ratings, wherein the second rating is an inferred rating determined with respect to the user;

determine a first weight for the first rating based on the first rating being provided by the user as opposed to being an inferred rating determined with respect to the user;

determine a second weight for the second rating based on the second rating being an inferred rating determined with respect to the user as opposed to being provided by the user, wherein the second weight is different than the first weight;

determine a first weighted rating for the first document based on the first rating and the first weight; and

determine a second weighted rating for the second document based on the second rating and the second weight,

wherein ranking the set of documents comprises ranking the set of documents based on the first weighted rating and the second weighted rating.

9. The system of claim 7, wherein determining the respective weights for each of the ratings comprises determining a weight for one inferred rating of the ratings based on one or more degrees of similarity between (i) a document associated with the one inferred rating and (ii) one or more other documents associated with one or more other ratings on which the one inferred rating is based.

10. The system of claim 7, wherein determining the respective weights for each of the ratings comprises determining a weight for one inferred rating of the ratings based on one or more degrees of similarity between (i) a document associated with the one inferred rating and (ii) one or more other documents for which the user has provided a rating on which the one inferred rating is based.

11. The system of claim 7, wherein the query includes a first metadata field specified by the user, and wherein determining the set of documents that are related to the query comprises selecting at least one document for inclusion in the set of documents based on a determination that a metadata field of the at least one document that corresponds to the first metadata field includes information relating to the query.

12. The system of claim 11, wherein the query includes at least one search term specified by the user for the first metadata field, and wherein selecting the at least one document comprises selecting the at least one document for inclusion in the set of documents based on a determination that a metadata field of the at least one document that corresponds to the first metadata field includes information relating to the at least one search term.