VISUAL METHOD AND APPARATUS FOR ENHANCING SEARCH RESULT NAVIGATION

• US 20070162443A1
• Filed: 01/04/2007
• Published: 07/12/2007
• Est. Priority Date: 01/12/2006
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Liu, Shixia, Su, Zhong
• Granted Patent: US 7,502,786 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/9038 Presentation of query results
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• 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

Abstract

A visual method for enhancing search result navigation, comprising: obtaining a first search result from a search engine; clustering the first search result to get clustering information; calculating the correlations between the clustering information and the ranked list of the first search result, and performing visualization processing on the clustering information; and displaying the visual cluster hierarchy and the ranked list of the first search result in a joint manner based on the correlations. When a cluster is selected, further searching is performed and the search result is clustered again. Using the present invention, through combining a traditional ranked list of search results and the visual cluster hierarchy of these search results to display them in a joint manner, a convenient way is provided for the web user to find the potential correlations between the visual cluster hierarchy and the ranked list of the search results. Besides, through dynamically searching and clustering more search results again, the web user may get more detailed and more accurate search results easily.

Claims

1. A visual method for enhancing search result navigation, comprising:

obtaining a first search result from a search engine;

clustering the first search result to get clustering information;

calculating the correlations between the clustering information and a ranked list of the first search result, and performing visualization processing on the clustering information; and

displaying the visual cluster hierarchy and the ranked list of the first search result in a joint manner based on the correlations.

2. The visual method for enhancing search result navigation according to claim 1, wherein the first search result contains a predetermined number of search result entries in the search results produced by the search engine based on a query.

3. The visual method for enhancing search result navigation according to claim 1, wherein displaying the visual cluster hierarchy and the ranked list of the first search result in a joint manner comprises one of the following:

a. when the pages of the ranked list of the first search result are displayed, the cluster in the visual cluster hierarchy that contains the most search result entries of the first search result is highlighted;

b. when the pages of the ranked list of the first search result are displayed, the cluster in the visual cluster hierarchy that contains the most search result entries of the first search result in the first page is highlighted;

c. when a search result entry in the ranked list of the first search result is selected, the cluster in the visual cluster hierarchy that contains the search result entry and the most search result entries of the first search result is highlighted;

d. when a search result entry in the ranked list of the first search result is selected, the cluster in the visual cluster hierarchy that contains the search result entry and the most search result entries of the first search result in the first page is highlighted; and

e. when a cluster in the visual cluster hierarchy is selected, the ranked list of the search result entries in the first search result that are contained in the cluster is displayed.

4. The visual method for enhancing search result navigation according to claim 1, wherein the step of clustering the first search result applies the Suffix Tree Clustering algorithm.

5. The visual method for enhancing search result navigation according to anyone of claim 1, further comprising:

selecting a cluster in the visual cluster hierarchy;

generating new query keywords and submitting them to the search engine;

producing a new search result based on the new query keywords by the search engine;

selecting a predetermined number of search result entries in the new search result to produce a second search result;

clustering the second search result to obtain sub-clustering information;

calculating the correlations between the sub-clustering information and the ranked list of the second search result, and performing visualization processing on the sub-clustering information;

displaying the visual sub-clustering information and the ranked list of the second search result in a joint manner based on the correlations; and

when a visual sub-clustering information item in the visual sub-clustering information is selected, repeating the above steps.

6. The visual method for enhancing search result navigation according to claim 5, wherein the visual cluster hierarchy and the visual sub-clustering information form a tree structure, wherein the clusters contained in the visual cluster hierarchy are taken as root nodes and the visual sub-clustering information items contained in the visual sub-clustering information are taken as branch nodes

7. The visual method for enhancing search result navigation according to claim 5, wherein the step of generating new query keywords comprises:

combining the current query keywords with the name of the selected cluster to generate new query keywords.

8. The visual method for enhancing search result navigation according to claim 5, wherein the step of generating new query keywords comprises:

collecting relevant documents;

determining keywords in the relevant documents; and

combining the keywords with the current query to produce a new query.

9. The visual method for enhancing search result navigation according to claim 8, wherein the relevant documents are the documents that have been read by the web user or the documents that belong to the selected cluster.

10. The visual method for enhancing search result navigation according to claim 8, wherein the step of determining keywords in the relevant documents comprises:

calculating weights of all words except stopwords in each document of the relevant documents with the following formula;

value_i=tf·

idf,

where value represents the weight of a word;

tf represents the frequency at which the word appears in the relevant documents;

idf=all_documents/keyword_documents, where all_documents represents the number of all the relevant documents, keyword_documents represents the number of the relevant documents that contain this word; and

determining the words with high weights as keywords.

11. A visual apparatus for enhancing search result navigation, comprising:

a dynamic cluster constructor configured to select search results coming from a search engine to get a first search result and dynamically cluster the first search result to generate clustering information;

a correlation processor configured to calculate the correlations between the clustering information and the ranked list of the first search result; and

a visualization engine configured to perform visualization processing on the clustering information to produce visual cluster hierarchy, and display the visual cluster hierarchy and the ranked list of the first search result on a browser in a joint manner based on the correlations.

12. The visual apparatus for enhancing search result navigation according to claim 11, wherein the dynamic cluster constructor comprises:

a search result selecting unit configured to select a predetermined number of search result entries from the received search result to generate a first search result and save the first search result; and

a clustering unit configured to cluster the first search result to generate the clustering information.

13. The visual apparatus for enhancing search result navigation according to claim 12, wherein the visualization engine displaying the visual cluster hierarchy and the ranked list of the first search result on a browser in a joint manner comprises any one of the following cases:

a. when the pages of the ranked list of the first search result are displayed, the cluster in the visual cluster hierarchy that contains the most search result entries of the first search result is highlighted;

b. when the pages of the ranked list of the first search result are displayed, the cluster in the visual cluster hierarchy that contains the most search result entries of the first search result in the first page is highlighted;

c. when a search result entry in the ranked list of the first search result is selected, the cluster in the visual cluster hierarchy that contains the search result entry and the most search result entries of the first search result is highlighted;

d. when a search result entry in the ranked list of the first search result is selected, the cluster in the visual cluster hierarchy that contains the search result entry and the most search result entries of the first search result in the first page is highlighted; and

e. when a cluster in the visual cluster hierarchy is selected, the ranked list of the search result entries in the first search result that are contained in the cluster is displayed.

14. The visual apparatus for enhancing search result navigation according to claim 12, wherein the clustering unit applies the Suffix Tree Clustering algorithm.

15. The visual apparatus for enhancing search result navigation according to claim 12, further comprising:

a keyword generator configured to generate new query keywords when selecting a cluster in the visual cluster hierarchy and send the keywords to the search engine through the dynamic cluster constructor;

wherein, the search engine performs searching based on the new query keywords generated by the keyword generator and returns a ranked list of the new search result;

the search result selecting unit of the dynamic cluster constructor selects a predetermined number of search result entries from the received ranked list of the new search result to generate a second search result and save it;

the clustering unit of the dynamic cluster constructor clusters the second search result to generate sub-clustering information;

the visualization engine visualizes the clustering information and the sub-clustering information into a tree structure, wherein the clustering information items contained in the clustering information are taken as root nodes and the sub-clustering information items contained in the sub-clustering information are taken as branch nodes, and the visualization engine also displays the visual cluster hierarchy and the ranked list of the second search result in a joint manner on the browser.

16. The visual apparatus for enhancing search result navigation according to claim 15, wherein the keyword generator combines the current query keywords with the name of the selected cluster to generate new query keywords.

17. The visual apparatus for enhancing search result navigation according to claim 15, wherein the keyword generator comprises:

a document collector configured to collect relevant documents;

a weight calculator configured to calculate weights of all words except stopwords in each one of the relevant documents; and

a keyword combiner configured to select the words with high weights and combine them with the current query keywords to generate new query keywords.

18. The visual apparatus for enhancing search result navigation according to claim 17, wherein the relevant documents are the documents that have been read by the web user or the documents that belong to the selected cluster.

19. The visual apparatus for enhancing search result navigation according to claim 17, wherein the weight calculator applies the following formula:

value_i=tf*idf;

where value represents the weight of a word;

tf represents the frequency at which the word appears in the relevant documents;

idf=all_documents/keyword_documents,

where all_documents represents the number of all the relevant documents keyword_documents represents the number of the relevant documents that contain this word.

20. A browser, comprising the visual apparatus for enhancing search result navigation comprising:

a dynamic cluster constructor configured to select search results coming from a search engine to get a first search result and dynamically cluster the first search result to generate clustering information;

a correlation processor configured to calculate the correlations between the clustering information and the ranked list of the first search result; and

a visualization engine configured to perform visualization processing on the clustering information to produce visual cluster hierarchy, and display the visual cluster hierarchy and the ranked list of the first search result on a browser in a joint manner based on the correlations.

21. A search engine, comprising the visual apparatus for enhancing search result navigation comprising:

a dynamic cluster constructor configured to select search results coming from a search engine to get a first search result and dynamically cluster the first search result to generate clustering information;

a correlation processor configured to calculate the correlations between the clustering information and the ranked list of the first search result; and

a visualization engine configured to perform visualization processing on the clustering information to produce visual cluster hierarchy, and display the visual cluster hierarchy and the ranked list of the first search result on a browser in a joint manner based on the correlations.

22. A program product, comprising:

program codes and carrying media for carrying said program codes, for implementating a method comprising;

obtaining a first search result from a search engine;

clustering the first search result to get clustering information;

calculating the correlations between the clustering information and a ranked list of the first search result, and performing visualization processing on the clustering information; and

displaying the visual cluster hierarchy and the ranked list of the first search result in a joint manner based on the correlations.