Reference Hub5
Query Recommendation for Improving Search Engine Results

Query Recommendation for Improving Search Engine Results

Hamada M. Zahera, Gamal F. El-Hady, W. F. Abd El-Wahed
ISBN13: 9781466638983|ISBN10: 1466638982|EISBN13: 9781466638990
DOI: 10.4018/978-1-4666-3898-3.ch004
Cite Chapter Cite Chapter

MLA

Zahera, Hamada M., et al. "Query Recommendation for Improving Search Engine Results." Information Retrieval Methods for Multidisciplinary Applications, edited by Zhongyu Lu, IGI Global, 2013, pp. 46-53. https://doi.org/10.4018/978-1-4666-3898-3.ch004

APA

Zahera, H. M., El-Hady, G. F., & El-Wahed, W. F. (2013). Query Recommendation for Improving Search Engine Results. In Z. Lu (Ed.), Information Retrieval Methods for Multidisciplinary Applications (pp. 46-53). IGI Global. https://doi.org/10.4018/978-1-4666-3898-3.ch004

Chicago

Zahera, Hamada M., Gamal F. El-Hady, and W. F. Abd El-Wahed. "Query Recommendation for Improving Search Engine Results." In Information Retrieval Methods for Multidisciplinary Applications, edited by Zhongyu Lu, 46-53. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-3898-3.ch004

Export Reference

Mendeley
Favorite

Abstract

As web contents grow, the importance of search engines become more critical and at the same time user satisfaction decreases. Query recommendation is a new approach to improve search results in web. In this paper a method is proposed that, given a query submitted to a search engine, suggests a list of queries that are related to the user input query. The related queries are based on previously issued queries, and can be issued by the user to the search engine to tune or redirect the search process. The proposed method is based on clustering processes in which groups of semantically similar queries are detected. The clustering process uses the content of historical preferences of users registered in the query log of the search engine. This facility provides queries that are related to the ones submitted by users in order to direct them toward their required information. This method not only discovers the related queries but also ranks them according to a similarity measure. The method has been evaluated using real data sets from the search engine query log.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.