Semantic-based grouping of search engine results using WordNet

Authors:
Reza Hemayati;Weiyi Meng;Clement Yu
Affiliations:
Department of Computer Science, State University of New York at Binghamton, Binghamton, NY;Department of Computer Science, State University of New York at Binghamton, Binghamton, NY;Department of Computer Science, University of Illinois at Chicago, Chicago, IL
Venue:
APWeb/WAIM'07 Proceedings of the joint 9th Asia-Pacific web and 8th international conference on web-age information management conference on Advances in data and web management
Year:
2007

Citing 9
Cited 6

Real life information retrieval: a study of user queries on the Web

ACM SIGIR Forum
Grouper: a dynamic clustering interface to Web search results

WWW '99 Proceedings of the eighth international conference on World Wide Web
Data clustering: a review

ACM Computing Surveys (CSUR)
A study of thresholding strategies for text categorization

Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
A Study of Approaches to Hypertext Categorization

Journal of Intelligent Information Systems
Learning to cluster web search results

Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
WISE-cluster: clustering e-commerce search engines automatically

Proceedings of the 6th annual ACM international workshop on Web information and data management
Word sense disambiguation in queries

Proceedings of the 14th ACM international conference on Information and knowledge management
Ontology-based automatic classification of web documents

ICIC'06 Proceedings of the 2006 international conference on Intelligent computing: Part II

Improving Web Search by Categorization, Clustering, and Personalization

ADMA '08 Proceedings of the 4th international conference on Advanced Data Mining and Applications
A Semantic Language for Querying Anonymous Web Sources

KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II
An algorithm for finding document concepts using semantic similarities from WordNet ontology

International Journal of Computational Vision and Robotics
Using semantic techniques to access web data

Information Systems
Reformulation of Telugu web query using word semantic relationships

Proceedings of the International Conference on Advances in Computing, Communications and Informatics
Non-syntactic word prediction for AAC

SLPAT '12 Proceedings of the Third Workshop on Speech and Language Processing for Assistive Technologies

Quantified Score

Hi-index	0.00

Visualization

Abstract

Terms used in search queries often have multiple meanings. Consequently, search results corresponding to different meanings may be retrieved, making identifying relevant results inconvenient and time-consuming. In this paper, we propose a new solution to address this issue. Our method groups the search results based on the different meanings of the query. It utilizes the semantic dictionary WordNet to determine the basic meanings or senses of each query term and similar senses are merged to improve grouping quality. Our grouping algorithm employs a combination of categorization and clustering techniques. Our experimental results indicate that our method can achieve high grouping accuracy.