DEMOGRAPHIC BASED CLASSIFICATION FOR LOCAL WORD WHEELING/WEB SEARCH

• US 20070255552A1
• Filed: 11/30/2006
• Published: 11/01/2007
• Est. Priority Date: 05/01/2006
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Thiesson, Bo, Church, Kenneth W.
• Granted Patent: US 7,778,837 B2
• Time in Patent Office: Days
• US Class Current: 704/8
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9537 Spatial or temporal dependent retrieval, e.g. spatiotemporal queries

Abstract

Systems and methods that create a classification of sentences in a language, and further construct associated local versions of language models, based on geographical location and/or other demographic criteria—wherein such local language models can be of different levels of granularity according to chosen demographic criteria. The subject innovation employs a classification encoder component that forms a classification (e.g. a tree structure) of sentences, and a local language models encoder component, which employs the classification of sentences in order to construct the localized language models. A decoder component can subsequently enable local word wheeling and/or local web search by blending k-best answers from local language models of varying demographic granularity that match users demographics. Hence, k-best matches for input data by users in one demographic locality can be different from k-best matches for the same input by other users in another locality.

Claims

1. A computer implemented system comprising the following computer executable components:

a classification encoder component that summarizes sentences into a classification based on demographics; and

a local language models encoder component that expands the classification to form localized language models, to facilitate a search for local interests.

2. The computer implemented system of claim 1, the local sentences in form of query logs.

3. The computer implemented system of claim 2, the classification in form of a tree structure to summarize query logs.

4. The computer implemented system of claim 1, further comprising a decoder component with an expansion component that evaluates input data via classification of local language models to produce a set of expansions.

5. The computer implemented system of claim 3, the tree structure with nodes that promote queries based on predetermined criteria.

6. The computer implemented system of claim 5, the predetermined criteria are significance test criteria.

7. The computer implemented system of claim 1, further comprising a local context component that provides information about a users locality in order to produce expansions relevant to local interests.

8. The computer implemented system of claim 1, the demographics based on at least one of time and space.

9. The computer implemented system of claim 3, the tree structure in form of a Kd-tree structure.

10. The computer implemented system of claim 1 further comprising an interface component that accepts input data from a user.

11. The computer implemented system of claim 1 further comprising an artificial intelligence component that facilitates smoothing of the classification.

12. A computer implemented method comprising the following computer executable acts:

summarizing sentences in form of a classification based on demographics; and

forming localized language models from the classification.

13. The computer implemented method of claim 12 further comprising smoothing the classification via moving the sentences among levels of the classification.

14. The computer implemented method of claim 12 the summarizing act comprising summarizing query logs in form of a tree structure with nodes.

15. The computer implemented method of claim 14, the forming act comprising forming local language model(s) for the nodes

16. The computer implemented method of claim 13 further comprising expanding an input based on the localized language.

17. The computer implemented method of claim 14 further comprising smoothing the tree structure based on predetermined criteria.

18. The computer implemented method of claim 15 further comprising promoting nodes based on predetermined significance criteria.

19. The computer implemented method of claim 15 further comprising obtaining k best matches in every node on a path from a leaf node to a root node of the tree, and combining the k best matches.

20. A computer implemented system comprising the following computer executable components:

means for forming a classification structure of local language models based on demographics;

means for creating localized language models from the classification; and

means for employing the classification structure of local language models to facilitate input expansions of local interest.