Automatic index term augmentation in document retrieval

• US 8,095,533 B1
• Filed: 11/09/2004
• Issued: 01/10/2012
• Est. Priority Date: 03/31/1999
• Status: Expired due to Fees

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: Ponte, Jay Michael
• Primary Examiner(s): PARDO, THUY N
• Application Number:
  US10/984,911
• Time in Patent Office: 2,618 Days
• Field of Search: 707/3, 707/4, 707/5, 707/100, 707/2, 707/6, 707/10, 707/101, 707/102, 707/103.Y, 707/104.1, 707/715, 707/708, 707/750, 707/753, 707/740, 707/741, 707/771, 707/711, 709/201, 715/501, 715/209, 704/9, 706/15
• US Class Current: 707/715
• 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: Y10S 707/944 Business related
• CPC Class Codes: Y10S 707/99931 Database or file accessing
• CPC Class Codes: Y10S 707/99932 Access augmentation or optimizing
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99934 Query formulation, input preparation, or translation
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access
• CPC Class Codes: Y10S 707/99936 Pattern matching access
• CPC Class Codes: Y10S 707/99945 Object-oriented database structure processing

Abstract

Disclosed are methods and systems for automatically assigning index terms to electronic documents such as Web pages or sites in a manner which may be used to facilitate the retrieval of electronic documents of interest. The method involves determining co-occurrences of terms in other documents with the electronic document, and selecting terms as index terms based upon those scores. The method permits the efficient retrieval of electronic documents.

Claims

1. A medium storing instructions executable by at least one processor, the instructions configured to cause the at least one processor to:

create a search query comprised of at least one term in a specific document;

apply the search query to a collection of documents;

select from the collection of documents a subset of documents, the subset of documents achieving the highest scores upon application of the search query;

select at least one term for use as at least one index term for the specific document from among terms in the subset of documents based upon the co-occurrence of terms in the subset of documents with terms in the specific document.

2. The medium of claim 1, wherein the search query comprises of all the terms in the specific document.

3. The medium of claim 1, further storing instructions to:

assign the selected at least one term to the specific document.

4. A medium storing instructions executable by at least one processor, the instructions configured to cause the at least one processor to:

select one or more index terms from a plurality of index terms;

identify one or more documents of a plurality of documents to which each of the one or more index terms has been assigned;

compare, for each of the one or more index terms, each of the identified documents to a specific document;

determine a score for each of the one or more index terms based on the comparing; and

assign the index term associated with the highest score to the specific document.

5. A computer-implemented method comprising:

selecting one or more index terms from a plurality of index terms;

identifying one or more documents of a plurality of documents to which each of the one or more index terms has been assigned;

comparing, for each of the one or more index terms, each of the identified documents to a specific document;

determining a score for each of the one or more index terms based on the comparing;

assigning the index term associated with the highest score to the specific document;

selecting a first category;

selecting one or more second categories assigned to a first supercategory;

comparing the first category and the one or more second categories;

computing a first score for the first supercategory based on the comparisons;

selecting one or more third categories assigned to a second supercategory;

comparing the first category and the one or more third categories;

computing a second score for the second supercategory based on the comparisons;

assigning the first category to the first supercategory when the first score is higher than the second score;

assigning the first category to the second supercategory when the second score is higher than the first score;

wherein the comparing of each of the identified documents to a specific document and the comparing the first category, comparing of the first category and the one or more second categories, comparing the one or more second categories, and the assigning the index term associated with the highest score to the specific document each include computing a likelihood ratio.

6. The method of claim 5, further comprising:

receiving a first user request;

presenting a set of categories based on the first user request, the set of categories including the first category;

receiving a second user request selecting the first category;

presenting a set of items associated with the first category;

presenting an advertisement, the advertisement associated with the first supercategory when the first category is assigned to the first supercategory and associated with the second supercategory when the first category is assigned to the second supercategory.

7. The method of claim 5, wherein the advertisement is a banner advertisement of web site.

8. The method of claim 5, wherein the set of items is a set of stores.

9. The method of claim 5, wherein the likelihood ratio is a log likelihood ratio.