# US 2010/0169244 A1 · Method and apparatus for using a discriminative classifier for processing a query

> Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt

- Number: US 2010/0169244 A1
- Document ID: US20100169244A1
- Status: Published application
- Kind: A1
- Application number: 12/347,513
- Filed: 2008-12-31
- Published: 2010-07-01
- Earliest claimed: 2008-12-31
- Assignees: AT&T Intellectual Property I, L.P.
- Inventors: Ilija Zeljkovic; Srinivas Bangalore; Patrick Haffner; Jay Wilpon
- Web page: https://patentgrep.com/patent/US20100169244A1

## CPC

- G06N 20/10: using kernel methods, e.g. support vector machines [SVM]
- G06F 16/3326: {using relevance feedback from the user, e.g. relevance feedback on documents, documents sets, document terms or passages}
- G06F 16/355: Creation or modification of classes or clusters
- G06F 16/93: Document management systems
- G06F 16/951: Indexing; Web crawling techniques
- G06F 16/9535: Search customisation based on user profiles and personalisation
- G06F 16/9538: Presentation of query results
- G06N 20/00: Machine learning
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)

## Abstract

A method and apparatus for using a classifier for processing a query are disclosed. For example, the method receives a query from a user, and processes the query to locate one or more documents in accordance with a search engine having a discriminative classifier, wherein the discriminative classifier is trained with a plurality of artificial query examples. The method then presents a result of the processing to the user.

## Claims

### Claim 1

A method for using a classifier for processing a query, comprising:
receiving a query from a user;
processing said query to locate one or more documents in accordance with a search engine having a discriminative classifier, wherein said discriminative classifier is trained with a plurality of artificial query examples; and
presenting a result of said processing to said user.

### Claim 2 (depends on 1)

The method of claim 1, further comprising:
receiving a feedback on said result presented to said user; and
retraining said discriminative classifier based on said feedback.

### Claim 3 (depends on 1)

The method of claim 1, further comprising:
retraining said discriminative classifier based on: updates to said one or more documents, or profiles of said one or more documents.

### Claim 4 (depends on 1)

The method of claim 1, wherein said discriminative classifier comprises a logistic regression classifier or a Support Vector Machine (SVM) classifier.

### Claim 5 (depends on 1)

The method of claim 1, wherein said discriminative classifier is trained based on one or more examples constructed from one or more names of said one or more documents, or from said one or more documents being within a class.

### Claim 6 (depends on 1)

The method of claim 1, wherein said discriminative classifier is trained based on one or more examples derived from one or more logs of previous searches.

### Claim 7 (depends on 1)

The method of claim 1, wherein said query is a speech based query.

### Claim 8 (depends on 1)

The method of claim 1, wherein said processing is based on meta information, wherein said meta information comprises one or more of: a user profile, past search results, or popularity of listings.

### Claim 9

A computer-readable medium having stored thereon a plurality of instructions, the plurality of instructions including instructions which, when executed by a processor, cause the processor to perform the steps of a method for using a classifier for processing a query, comprising:
receiving a query from a user;
processing said query to locate one or more documents in accordance with a search engine having a discriminative classifier, wherein said discriminative classifier is trained with a plurality of artificial query examples; and
presenting a result of said processing to said user.

### Claim 10 (depends on 9)

The computer-readable medium of claim 9, further comprising:
receiving a feedback on said result presented to said user; and
retraining said discriminative classifier based on said feedback.

### Claim 11 (depends on 9)

The computer-readable medium of claim 9, further comprising:
retraining said discriminative classifier based on: updates to said one or more documents, or profiles of said one or more documents.

### Claim 12 (depends on 9)

The computer-readable medium of claim 9, wherein said discriminative classifier comprises a logistic regression classifier or a Support Vector Machine (SVM) classifier.

### Claim 13 (depends on 9)

The computer-readable medium of claim 9, wherein said discriminative classifier is trained based on one or more examples constructed from one or more names of said one or more documents, or from said one or more documents being within a class.

### Claim 14 (depends on 9)

The computer-readable medium of claim 9, wherein said discriminative classifier is trained based on one or more examples derived from one or more logs of previous searches.

### Claim 15 (depends on 9)

The computer-readable medium of claim 9, wherein said query is a speech based query.

### Claim 16 (depends on 9)

The computer-readable medium of claim 9, wherein said processing is based on meta information, wherein said meta information comprises one or more of: a user profile, past search results, or popularity of listings.

### Claim 17

An apparatus for using a classifier for processing a query, comprising:
means for receiving a query from a user;
means for processing said query to locate one or more documents in accordance with a search engine having a discriminative classifier, wherein said discriminative classifier is trained with a plurality of artificial query examples; and
means for presenting a result of said processing to said user.

### Claim 18 (depends on 17)

The apparatus of claim 17, further comprising:
means for receiving a feedback on said result presented to said user; and
means for retraining said discriminative classifier based on said feedback.

### Claim 19 (depends on 17)

The apparatus of claim 17, further comprising:
means for retraining said discriminative classifier based on: updates to said one or more documents, or profiles of said one or more documents.

### Claim 20 (depends on 17)

The apparatus of claim 17, wherein said discriminative classifier comprises a logistic regression classifier or a Support Vector Machine (SVM) classifier.