CONTENT DATA INDEXING WITH CONTENT ASSOCIATIONS

• US 20070282822A1
• Filed: 08/20/2007
• Published: 12/06/2007
• Est. Priority Date: 07/01/2002
• Status: Active Grant

• Current Assignee: Zhigu Holdings Limited
• Original Assignee: Microsoft Corporation
• Inventors: Jayanti, Harish, Anderson, Christopher
• Granted Patent: US 7,970,768 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/48 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
• CPC Class Codes: Y10S 707/917 Text
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access
• 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

Abstract

A full text indexing system is provided for processing content associated with data applications such as encyclopedia and dictionary applications. A build process collects data from various sources, processes the data into constituent parts, including alternative word sets, and stores the constituent parts in structured database tables. A run-time process is used to query the database tables and the results in order to provide effective matches in an efficient manner. Run-time processing is optimized by preprocessing all steps that are query-independent during the build process. A double word table representing all possible word pair combinations for each index entry and an alternative word table are used to further optimize runtime processing.

Claims

1. In a computing system having access to multiple content entities, each content entity including searchable content, a method for building a database for facilitating searching and retrieving of content entities in an efficient manner that returns results of content entities expected to be found, the method comprising:

creating a skeleton database for storing a search index table and one or more other tables for facilitating a search for content entities within one or more content sources;

inserting index data into the skeleton database, the index data including index entries pointing to content within the one or more content sources;

processing content entities from a first content source and inserting data associated with the content entities into the search index table;

adding to the skeleton database associations between content entities of the one or more content sources and processing related content entities identified by the associations; and

outputting the skeleton database into an output file that includes the search index table and the one or more other tables, and detaching the output file from a build server used to create the skeleton database.

2. A method as recited in claim 1, further comprising:

adding to the skeleton database the one or more other tables, wherein the one or more other tables include rules on how to process the content within the one or more content sources.

3. A method as recited in claim 2, wherein the one or more other tables includes a class table.

4. A method as recited in claim 2, wherein the one or more other tables includes a class/entity table.

5. A method as recited in claim 2, wherein the one or more other tables includes a entity table.

6. A method as recited in claim 1, wherein adding to the skeleton database associations between content entities of the one or more content sources includes adding forward associations.

7. A method as recited in claim 1, wherein adding to the skeleton database associations between content entities of the one or more content sources includes adding forward associations between content entities.

8. A method as recited in claim 1, wherein adding to the skeleton database associations between content entities of the one or more content sources includes adding backward associations between content entities.

9. A method as recited in claim 1, further comprising adding text to the database, the text corresponding to the processed content entities.

10. A method as recited in claim 1, further comprising processing related content entities, the related content entities being included in hierarchical lists of content related to a particular content entity.

11. A method as recited in claim 1, further comprising storing index key words in the search index table and one or more other tables, and removing unnecessary entries in the tables.

12. A computer-readable storage medium having stored thereon computer-executable instructions that, when executed by a processor, cause a computing system to perform the method of claim 10.

13. In a computing system having access to multiple content entities, each content entity including searchable content, a method performing a run-time search for tokens related to key terms input in a user query, the method comprising:

receiving a user query, the user query including one or more key terms input by a user for searching and retrieving content entities;

converting the user query to a tokenized query;

sending the original user query and the tokenized query to a database;

in the database, conducting an exact match on the user query;

in the database, conducting an exact match on the tokenized query;

identifying all terms in the user query and tokenized query which are valid words in the one or more search indexes;

searching the one or more search indexes with the key terms of the user query; and

returning to a user a result set of all content entities matching the user query and the tokenized query.

14. A method as recited in claim 13, further comprising sending the user query to a web service.

15. A method as recited in claim 13, wherein identifying all key terms in the user query and tokenized query which are valid words in the one or more search indexes includes looking up each key term and token in a search word table.

16. A method as recited in claim 13, further comprising creating word pairs from all valid words, and searching a search content double word table with the word pairs.

17. A method as recited in claim 16, further comprising searching a search content word table with the key terms.

18. A method as recited in claim 13, wherein returning to a user a result set of all content entities matching the user query and the tokenized query comprises returning a plurality of result sets to a web service.

19. A method as recited in claim 18, further comprising merging the plurality of result sets into a single list.

20. A method as recited in claim 19, further comprising removing all duplicate content entities from the single list.