More Web Proxy on the site http://driver.im/

research-article

A personalized result merging method for metasearch engine

Authors:

Boyu ZhouAuthors Info & Claims

ICSCA '17: Proceedings of the 6th International Conference on Software and Computer Applications

Pages 203 - 207

https://doi.org/10.1145/3056662.3056698

Published: 26 February 2017 Publication History

Abstract

Metasearch engine integrates the search results from multiple sources, and improves recall in the big data environment. Result merging is a key component which will greatly affect the effectiveness of a metasearch engine. Great progress has been made in this area, however few studies have focused on providing personalized results for different users. This paper proposes a personalized method for merging results of metasearch engine according to a variety of factors, including the user interest distribution, the total number of component search engines exploited, the number of the results that each engine returned, the ranking position of document in each search engine and the number of component search engines who returned the document. Compared with the Borda Fuse method and rCombMNZ method, experimental results show that the proposed model performs better on mean average precision, improving the significance of documents which seldom occurred but are important to the user. By considering the distribution of user interest, the method also has ability of providing personalized result for different users. It is feasible to provide the useful search results more effectively.

References

[1]

Qingshan, Li., et al. 2015.Personalization mechanism in an intelligent agent-based metasearch engine. ScientiaSinica, 45, 5(Aug, 2015), 602--622.

[2]

Selberg, Erik, and O. Etzioni. 1995.Multi-Service Search and Comparison Using the MetaCrawler.In Proceedings of the 4th international World Wide Web conference, Boston, United States, 195--208.

[3]

Aslam, Javed A., and M. Montague. 2001. Models for metasearch. In Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval, New Orleans, USA, 275--284.

Digital Library

[4]

Diaz, Elizabeth D., A. De, and V. Raghavan. 2005. A Comprehensive OWA-Based Framework for Result Merging in Metasearch, Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. Springer Berlin Heidelberg, 193--201.

Digital Library

[5]

Yager, Ronald R. 1988.On ordered weighted averaging aggregation operators in multi criteria decision making. IEEE Transactions on Systems, Man, and Cybernetics, 18, 1(Feb, 1988), 183--190.

Digital Library

[6]

Yager, Ronald R. 1996. Quantifier guided aggregation using OWA operators, International Journal of Intelligent Systems, 11,1(Jan, 1996),49--73. <49::AID-INT3>3.0.CO;2-Z

[7]

Yager, R. R., and V. Kreinovich. 1999.On how to merge sorted lists coming from different web search tools. Soft Computing, 3, 2(Sept, 1999), 83--88.

[8]

De, A., and E. D. Diaz. 2011.A Fuzzy Ordered Weighted Average (OWA) Approach to Result Merging for Metasearch Using the Analytical Network Process.2nd International Conference on Emerging Applications of Information Technology IEEE, Washington, USA, 17--20.

Digital Library

[9]

Wu, Shengli, and F. Crestani. 2004. Shadow document methods of results merging. In Proceedings of the 19th ACM Symposium on Applied Computing, Nicosia, Cyprus, 1067--1072.

Digital Library

[10]

Fox, Edward A., and J. A. Shaw. 1993. Combination of Multiple Searches. In Proceedings of the 2nd Text Retrieval Conference, Gaithersburg, USA, 243--252. DOI= http://dx.doi.org/10.1.1.52.5586

[11]

Howe, A. E. 1997. SavvySearch: Ametasearch engine that learns which search engines toquery.AI Magazine, 18,2(Nov, 1997), 19--25.

[12]

Selberg, E., and O. Etzioni. 2002. The MetaCrawler architecture for resource aggregation on the Web. IEEE Expert, 12,1(Aug, 2002), 11--14.

[13]

Renda, M. Elena, and U. Straccia. 2003. Web Metasearch: Rank vs. Score Based Rank Aggregation Methods. ACM Symposium on Applied Computing, New York, USA, 841--846.

Digital Library

[14]

Lu, Yiyao, et al. 2005. Evaluation of Result Merging Strategies for Metasearch Engines. Web Information Systems Engineering - WISE 2005, International Conference on Web Information Systems Engineering, New York, USA, 3806(Nov, 2095), 53--66.

Digital Library

[15]

Fuyong, Yuan, and W. Jin-Dong. 2009. An Implemented Rank Merging Algorithm for Meta Search Engine. International Conference on Research Challenges in Computer Science IEEE Computer Society, Washington, USA, 191--193.

Digital Library

[16]

Liu, Fang, Clement Yu, and Weiyi Meng. 2004. Personalized Web Search for Improving Retrieval Effectiveness. IEEE Transactions on knowledge and data engineering, 16, 1(Jan, 2004), 28--39.

Digital Library

[17]

Spink, Amanda. 2002. A user-centered approach to evaluating human interaction with Web search engines: an exploratory study. Information Processing & Management, 38, 3(May, 2002), 401--426.

Digital Library

[18]

Craswell N. 2009.Precision at n. Springer, US.

[19]

Zuva K, Zuva T. 2012. Evaluation of Information Retrieval Systems. International Journal of Computer Science & Information Techmology, 4,3(Jun, 2012),35--43.

Cited By

Akritidis LFevgas ABozanis PManolopoulos Y(2022)An unsupervised distance-based model for weighted rank aggregation with list pruningExpert Systems with Applications10.1016/j.eswa.2022.117435202(117435)Online publication date: Sep-2022
https://doi.org/10.1016/j.eswa.2022.117435
Wang MLi QLin Y(2020)An Organizational Structure and Self-adaptive Mechanism for Holonic Multi-Agent SystemsIEEE Access10.1109/ACCESS.2020.3014694(1-1)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3014694
Dimri NKaul HGupta D(2018)MetaXplorer: an intelligent and adaptable metasearch engine using a novel ordered weighted averaging operatorInternational Journal of System Assurance Engineering and Management10.1007/s13198-018-0746-59:6(1315-1325)Online publication date: 8-Sep-2018
https://doi.org/10.1007/s13198-018-0746-5

Index Terms

A personalized result merging method for metasearch engine
1. Information systems
  1. Information retrieval
    1. Retrieval models and ranking
      1. Rank aggregation

Recommendations

Using Online Relevance Feedback to Build Effective Personalized Metasearch Engine
WISE '01: Proceedings of the Second International Conference on Web Information Systems Engineering (WISE'01) Volume 1 - Volume 1

Metasearch Engine is popular for facilitating users' queries over multiple search engines and increasing the coverage of the WWW. How to rank the merged results becomes crucial for the success of metasearch engines. Many current metasearch engines have ...
Discovering the representative of a search engine
CIKM '01: Proceedings of the tenth international conference on Information and knowledge management

Given a large number of search engines on the Internet, it is difficult for a person to determine which search engines could serve his/her information needs. A common solution is to construct a metasearch engine on top of the search engines. Upon ...
Discovering the representative of a search engine
CIKM '02: Proceedings of the eleventh international conference on Information and knowledge management

Given a large number of search engines on the Internet, it is difficult for a person to determine which search engines could serve his/her information needs. A common solution is to construct a metasearch engine on top of the search engines. Upon ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Other conferences

ICSCA '17: Proceedings of the 6th International Conference on Software and Computer Applications

February 2017

339 pages

ISBN:9781450348577

DOI:10.1145/3056662

Conference Chairs:
Vitaliy Mezhuyev
Universiti Malaysia Pahang, Malaysia
,
Luigi Benedicenti
University of Regina, Canada

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 February 2017

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities of China
Pre-Research Project of the Thirteenth Five-Year-Plan of China

Conference

ICSCA 2017

ICSCA 2017: 2017 6th International Conference on Software and Computer Applications

February 26 - 28, 2017

Bangkok, Thailand

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
115
Total Downloads

Downloads (Last 12 months)1
Downloads (Last 6 weeks)0

Reflects downloads up to 12 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Akritidis LFevgas ABozanis PManolopoulos Y(2022)An unsupervised distance-based model for weighted rank aggregation with list pruningExpert Systems with Applications10.1016/j.eswa.2022.117435202(117435)Online publication date: Sep-2022
https://doi.org/10.1016/j.eswa.2022.117435
Wang MLi QLin Y(2020)An Organizational Structure and Self-adaptive Mechanism for Holonic Multi-Agent SystemsIEEE Access10.1109/ACCESS.2020.3014694(1-1)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3014694
Dimri NKaul HGupta D(2018)MetaXplorer: an intelligent and adaptable metasearch engine using a novel ordered weighted averaging operatorInternational Journal of System Assurance Engineering and Management10.1007/s13198-018-0746-59:6(1315-1325)Online publication date: 8-Sep-2018
https://doi.org/10.1007/s13198-018-0746-5

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents