A New Query Expansion Approach for Improving Web Search Ranking

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Stephen Akuma 1,* Promise Anendah 1

1. Institution: Department of Mathematics and Computer Science, Benue State University

* Corresponding author.

DOI: https://doi.org/10.5815/ijitcs.2023.01.05

Received: 23 Aug. 2022 / Revised: 2 Oct. 2022 / Accepted: 11 Nov. 2022 / Published: 8 Feb. 2023

Index Terms

Search Engine, Query Expansion, Relevance Feedback, Information Retrieval, WWQE Model


Information systems have come a long way in the 21st century, with search engines emerging as the most popular and well-known retrieval systems. Several techniques have been used by researchers to improve the retrieval of relevant results from search engines. One of the approaches employed for improving relevant feedback of a retrieval system is Query Expansion (QE). The challenge associated with this technique is how to select the most relevant terms for the expansion. In this research work, we propose a query expansion technique based on Azak & Deepak's WWQE model. Our extended WWQE technique adopts Candidate Expansion Terms selection with the use of in-links and out-links. The top two relevant Wikipedia articles from the user's initial search were found using a custom search engine over Wikipedia. Following that, we ranked further Wikipedia articles that are semantically connected to the top two Wikipedia articles based on cosine similarity using TF-IDF Vectorizer. The expansion terms were then taken from the top 5 document titles. The results of the evaluation of our methodology utilizing TREC query topics (126-175) revealed that the system with extended features gave ranked results that were 11% better than those from the system with unexpanded queries.

Cite This Paper

Stephen Akuma, Promise Anendah, "A New Query Expansion Approach for Improving Web Search Ranking", International Journal of Information Technology and Computer Science(IJITCS), Vol.15, No.1, pp.42-55, 2023. DOI:10.5815/ijitcs.2023.01.05


[1]D. Di Caprio, F.J. Santos-Arteaga and M. Tavana, "An information retrieval benchmarking model of satisficing and impatient users’ behavior in online search environments," Expert Syst.Appl., vol. 191, 1 April 2022, pp. 116352.
[2]A. Undu and S. Akuma, "Investigating the Usability of a University Website from the Users’ Perspective: An Empirical Study of Benue State University Website," International Journal of Computer and Information Engineering, vol. 12(10), pp. 922-929.
[3]M. Bouchakwa, Y. Ayadi and I. Amous, "An ambiguous tag-based query reformulation technique for an effective semantic-based social image research," Procedia Computer Science, vol. 176, 2020, pp. 508-520.
[4]J. Chen, J. Mao, Y. Liu, F. Zhang, M. Zhang and S. Ma, "Towards a Better Understanding of Query Reformulation Behavior in Web Search,", pp. 743-755.
[5]J. Mao, Y. Liu, K. Zhou, J. Nie, M. Zhang, S. Ma, J. Sun and H. Luo, "When does Relevance Mean Usefulness and User Satisfaction in Web Search?" SIGIR '16 Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, July 17 -21, 2016, pp. 463-472.
[6]P. Ankalkoti, "Survey on Search Engine Optimization Tools & Techniques," Imperial journal of interdisciplinary research, vol. 3.
[7]S. Akuma, C. Jayne, R. Iqbal and F. Doctor, "Implicit predictive indicators: Mouse activity and dwell time," IFIP Advances in Information and Communication Technology, vol. 436, pp. 162-171.
[8]U. Kruschwitz, D. Lungley, M.-. Albakour and D. Song, "Deriving query suggestions for site search," J Am Soc Inf Sci Tec, vol. 64, pp. 1975-1994.
[9]M. Sanderson and W.B. Croft, "The History of Information Retrieval Research," Proceedings of the IEEE, 100(Special Centennial Issue), pp. 1444-1451.
[10]M. Nagpal and J.A. Petersen, "Keyword Selection Strategies in Search Engine Optimization: How Relevant is Relevance?" J.Retail., vol. 97, no. 4, December 2021, pp. 746-763.
[11]Stephen Akuma, Rahat Iqbal, "Development of Relevance Feedback System using Regression Predictive Model and TF-IDF Algorithm", International Journal of Education and Management Engineering(IJEME), Vol.8, No.4, pp.31-49, 2018.DOI:10.5815/ijeme.2018.04.04
[12]T. Kucukyilmaz, "Exploiting temporal changes in query submission behavior for improving the search engine result cache performance," Information Processing & Management, vol. 58, no. 3, May 2021, pp. 102533.
[13]D.K. Sharma, R. Pamula and D.S. Chauhan, "A Comparative Analysis of Fuzzy Logic Based Query Expansion Approaches for Document Retrieval," In M. Singh, P. K. Gupta, V. Tyagi, J. Flusser, & T. Ören (Eds.), Advances in Computing and Data Sciences, vol. 906, pp. 336-345.
[14]H.K. Azad and A. Deepak, "A novel model for query expansion using pseu-do-relevant web knowledge," Inf.Sci., August 2019.
[15]C. Carpineto and G. Romano, '"A Survey of Automatic Query Expansion in Information Retrieval," Information Retrieval. ACM Comput. Surv., vol. 44(1).
[16]J. Ooi, M. Xiuqin, Q. Hongwu and S.C. Liew, "A survey of query expansion, query suggestion and query refinement techniques,", pp. 112-117.
[17]N.J. Belkin, D. Kelly, G. Kim, J.Y. Kim, H.J. Lee, G. Muresan, M.C. Tang, X.J. Yuan and C. Cool, "Query Length in Interactive Information Retrieval,", pp. 205-2012.
[18]H.K. Azad and A. Deepak, "A new approach for query expansion using Wikipedia and WordNet," Inf.Sci., vol. 492, August 2019, pp. 147-163.
[19]D. Pal, M. Mitra and K. Datta, "Improving query expansion using WordNet," J. Assoc. Inf. Sci. Technol, vol. 65(12), pp. 2469-2478.
[20]D. Roy, D. Paul, M. Mitra and U. Garain, "Using Word Embeddings for Automatic Query Expansion," ArXiv:1606.07608 [Cs].
[21]A. Keikha, F. Ensan and E. Bagheri, '"Query expansion using pseudo relevance feedback on wikipedia," Journal of Intelligent Information Systems, vol. 50(1), pp. 1-24.
[22]R.K. Bisht and I.P. Bisht, "Effect of Query Formation on Web Search Engine Results," International Journal on Natural Language Computing, vol. 2(1), pp. 31-36.
[23]S. Akuma and R. Iqbal, "Investigation of Students’ Information Seeking Behaviour," International Journal of Advanced Research in Computer Science and Software Engineering, vol. 2, no. 12, pp. 28-35.
[24]C. Claudio, D. Renato, R. Giovanni and B. Brigitte, "An Information Theoretic Approach to Automatic Query Expansion," ACM Transactions on Information Systems, vol. 19, pp. 1-17.
[25]D.K. Sharma, R. Pamula and D.S. Chauhan, "Query expansion – Hybrid framework using fuzzy logic and PRF," Measurement, vol. 198, July 2022, pp. 111300.
[26]D.B. Jake, H. HIlary and S. Maria, "User Preference and Search Engine Latency,".
[27]C. Xiong and J. Callan, "Query Expansion with Freebas,", pp. 111-120.
[28]T. Russell-Rose, P. Gooch and U. Kruschwitz, "Interactive query expansion for professional search applications," Business Information Review, vol. 38(3), pp. 127-137.
[29]Q. Yonggang and H. Frei, "Concept based query expansion,", pp. 160-169.
[30]C. Hang, W. Ji-Rong, N. Jian-Yun and M. Wei-Ying, "Probabilistic query expansion using query logs,", pp. 325-332.
[31]B.M. Fonseca, P. Golgher, B. Pôssas, B. Ribeiro-Neto and N. Ziviani, "Concept-based interactive query expansion," Concept-based interactive query expansion, pp. 696.
[32]S. Riezler, Y. Liu and A. Vasserman, "Translating queries into snippets for improved query expansion," Proceedings of the 22nd International Conference on Computational Linguistics - COLING ’08, pp. 737-744.
[33]A. Keikha, F. Ensan and E. Bagheri, "Query expansion using pseudo relevance feedback on wikipedia," Journal of Intelligent Information Systems, vol. 50(1), pp. 1-24.
[34]TREC, "TREC Queries 126 – 175,", vol. 2022.