Category-based search

• US 8,862,580 B1
• Filed: 10/10/2011
• Issued: 10/14/2014
• Est. Priority Date: 03/01/2004
• Status: Active Grant

• Current Assignee: Huawei Technologies Co., Ltd. (Huawei Investment & Holding Co., Ltd.)
• Original Assignee: Radix Holdings, LLC
• Inventors: Emigh, Aaron T., Roskind, James A.
• Primary Examiner(s): MORRISON, JAY A
• Application Number:
  US13/270,221
• Time in Patent Office: 1,100 Days
• Field of Search: None
• US Class Current: 707/731
• CPC Class Codes: G06F 16/245 Query processing
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/353 into predefined classes
• CPC Class Codes: G06F 16/986 Document structures and storage, e.g. HTML extensions

Abstract

In some embodiments, techniques for searching comprise providing a user interface, wherein the user interface is associated with an input area and a selector, receiving a search term and a desired category simultaneously, wherein the search term is associated with the input area and the category is associated with the selector, determining a plurality of documents, wherein each of the plurality of documents is associated with the search term and the category, and providing a search result, wherein the search result is associated with the plurality of documents.

Claims

1. A method for searching, comprising:

processing a second plurality of documents with a plurality of programmatic classifiers, wherein each of the programmatic classifiers receives documents from among the second plurality of documents as an input, and determines for each respective document, based at least in part on content of the document, whether the document belongs to a category associated with each respective programmatic classifier, wherein processing the second plurality of documents with the plurality of programmatic classifiers includes categorizing a first plurality of documents as belonging to a first category;

providing a user interface, wherein the user interface is associated with an input area and a selector;

receiving a search term and a desired category simultaneously, wherein the search term is associated with the input area and the desired category is associated with the selector, and wherein the desired category is the first category;

determining a third plurality of documents, wherein each of the third plurality of documents is associated with the search term and wherein each of the third plurality of documents has been determined to belong to the first category; and

providing a search result, wherein the search result is associated with the third plurality of documents.

2. The method of claim 1, further comprising constructing a search query, wherein the search query is associated with the search term and the desired category, providing the search query, and receiving the search result.

3. The method of claim 1, wherein the second plurality of documents is associated with a crawling of the Internet.

4. The method of claim 1, further comprising combining the search results with sponsored results.

5. The method of claim 1, further comprising classifying the second plurality of documents into a plurality of categories, wherein the first category is one of the plurality of categories.

6. The method of claim 1, wherein at least one of the plurality of programmatic classifiers is a Bayesian classifier.

7. The method of claim 1, wherein at least one of the plurality of programmatic classifiers is a support vector machine.

8. The method of claim 1, wherein the content of the document includes a specification of a classification for the document, and wherein the document is classified according to the specification of the classification.

9. The method of claim 1, further comprising training at least one of the plurality of classifiers using a training corpus, wherein the training corpus includes a plurality of training documents, wherein each of the plurality of training documents is associated with at least one category.

10. The method of claim 1, wherein the selector includes a pulldown menu.

11. The method of claim 1, wherein the selector includes radio buttons.

12. The method of claim 1, wherein the selector includes checkboxes.

13. The method of claim 1, further comprising determining the search result, wherein determining the search result includes searching an inverted index associated with the desired category.

14. A system for searching, comprising:

a processor configured to;

processing a second plurality of documents with a plurality of programmatic classifiers, wherein each of the programmatic classifiers receives documents from among the second plurality of documents as an input, and determines for each respective document, based at least in part on content of the document, whether the document belongs to a category associated with each respective programmatic classifier, wherein processing the second plurality of documents with the plurality of programmatic classifiers includes categorizing a first plurality of documents as belonging to a first category;

provide a user interface, wherein the user interface is associated with an input area and a selector;

receive a search term and a desired category simultaneously, wherein the search term is associated with the input area and the desired category is associated with the selector, and wherein the desired category is the first category;

determine a third plurality of documents, wherein each of the third plurality of documents is associated with the search term and wherein each of the third plurality of documents has been determined to belong to the first category; and

provide a search result, wherein the search result is associated with the third plurality of documents; and

a memory coupled with the processor, wherein the memory provides instructions to the processor.

15. The system of claim 14, wherein the processor is further configured to classify the second plurality of documents into a plurality of categories, wherein the first category is one of the plurality of categories.

16. The system of claim 14, wherein the processor is further configured to train at least one of the plurality of classifiers using a training corpus, wherein the training corpus includes a plurality of training documents, wherein each of the plurality of training documents is associated with at least one category.

17. A computer program product for searching, the computer program product being embodied in a computer readable storage medium and comprising computer instructions for:

processing a second plurality of documents with a plurality of programmatic classifiers, wherein each of the programmatic classifiers receives documents from among the second plurality of documents as an input, and determines for each respective document, based at least in part on content of the document, whether the document belongs to a category associated with each respective programmatic classifier, wherein processing the second plurality of documents with the plurality of programmatic classifiers includes categorizing a first plurality of documents as belonging to a first category;

providing a user interface, wherein the user interface is associated with an input area and a selector;

receiving a search term and a desired category simultaneously, wherein the search term is associated with the input area and the desired category is associated with the selector, and wherein the desired category is the first category;

determining a third plurality of documents, wherein each of the third plurality of documents is associated with the search term and wherein each of the third plurality of documents has been determined to belong to the first category; and

providing a search result, wherein the search result is associated with the third plurality of documents.

18. The computer program product of claim 17, wherein the computer program product further comprises computer instructions for classifying the second plurality of documents into a plurality of categories, wherein the first category is one of the plurality of categories.

19. The computer program product of claim 17, further comprising computer instructions for training at least one of the plurality of classifiers using a training corpus, wherein the training corpus includes a plurality of training documents, wherein each of the plurality of training documents is associated with at least one category.

20. The computer program product of claim 17, further comprising computer instructions for constructing a search query, wherein the search query is associated with the search term and the desired category, providing the search query, and receiving the search result.