A Survey of Query Expansion Methods to Improve Relevant Search Engine Results

Nuhu Yusuf, Mohd Amin Mohd Yunus, Norfaradilla Wahid, Aida Mustapha, Mohd Najib Mohd Salleh

Abstract


Due to large volumes of documents available for retrieval in a search database, an intelligent method is required to retrieve relevant search results. Query expansion is one of such methods widely used in retrieving pertinent results of various search domains. The increased amount of information stored in a search engine database requires the use of query expansion. A query expansion deals with expanding the query by adding additional information to the query for effective retrieving relevant results. Recently, many query expansion techniques have been proposed to addresses the vocabulary mismatch problem that may arise in the information retrieval system. However, these techniques still have low precision results. This paper presents a systematic review of query expansion research from 1999 to 2018. The paper reviewed and discussed 573 research papers on query expansion methods and their application areas. It focuses only on the query expansion in text retrieval of search engines. This review's primary goal is to provide a broad overview of query expansion research and view how research approaches changed. The research paper analyzed and presented the contributions of each query expansion study. It also identifies major application areas of query expansions and their future opportunities. The finding of this study indicates a trend towards using semantic-ontology and pseudo-relevant feedbacks methods. This work will be beneficial to query expansion researchers in extending future work on query expansion research.

Keywords


Query expansion; query expansion methods; query expansion methods; search engine; information retrieval.

Full Text:

PDF

References


J. Bhogal, A. Macfarlane, and P. Smith, “A review of ontology based query expansion,” Inf. Process. Manag., vol. 43, no. 4, pp. 866–886, 2007.

C. Carpineto and G. Romano, “A Survey of Automatic Query Expansion in Information Retrieval,” ACM Comput. Surv., vol. 44, no. 1, pp. 1–50, 2012.

J. Ooi, X. Ma, H. Qin, and S. C. Liew, “A survey of query expansion, query suggestion and query refinement techniques,” 2015 4th Int. Conf. Softw. Eng. Comput. Syst. ICSECS 2015 Virtuous Softw. Solut. Big Data, pp. 112–117, 2015.

M. A. Zingla, C. Latiri, P. Mulhem, C. Berrut, and Y. Slimani, “Hybrid query expansion model for text and microblog information retrieval,” Inf. Retr. J., vol. 21, no. 4, pp. 337–367, 2018.

M. A. Zingla, L. Chiraz, and Y. Slimani, “Short Query Expansion for Microblog Retrieval,” Procedia Comput. Sci., vol. 96, pp. 225–234, 2016.

N. Zhang, J. Wang, M. Yutao, H. Keqing, L. Zheng, and L. Xiaoqing(Frank), “Web service discovery based on goal-oriented query expansion,” J. Syst. Softw., vol. 142, pp. 73–91, 2018.

I. Moawad, W. Alromima, and R. Elgohary, “Bi-Gram Term Collocations-based Query Expansion Approach for Improving Arabic Information Retrieval,” Arab. J. Sci. Eng., vol. 43, no. 12, pp. 7705–7718, 2018.

F. C. Fernández-Reyes, J. Hermosillo-Valadez, and M. Montes-y-Gómez, “A Prospect-Guided global query expansion strategy using word embeddings,” Inf. Process. Manag., vol. 54, no. 1, pp. 1–13, 2018.

J. Singh and A. Sharan, “Rank fusion and semantic genetic notion based automatic query expansion model,” Swarm Evol. Comput., vol. 38, no. September 2017, pp. 295–308, 2018.

N. Yusuf, M. A. M. Yunus, and N. Wahid, “A Comparative Analysis of Web Search Query: Informational Vs Navigational Queries,” Int. J. Adv. Sci. Eng. Inf. Technol., vol. 9, no. 1, 2019.

Y. Gupta and A. Saini, “A novel Fuzzy-PSO term weighting automatic query expansion approach using combined semantic filtering,” Knowledge-Based Syst., vol. 136, pp. 97–120, 2017.

F. Pérez, J. Font, L. Arcega, and C. Cetina, “Automatic query reformulations for feature location in a model-based family of software products,” Data Knowl. Eng., vol. 116, no. April, pp. 159–176, 2018.

G. Chandra and S. K. Dwivedi, “Query expansion based on term selection for Hindi - English cross lingual IR,” J. King Saud Univ. - Comput. Inf. Sci., 2017.

L. Diao, H. Yan, F. Li, S. Song, G. Lei, and F. Wang, “The research of query expansion based on medical terms reweighting in medical information retrieval,” EURASIP J. Wirel. Commun. Netw., vol. 2018, no. 1, p. 105, Dec. 2018.

R. Crimp and A. Trotman, “Automatic Term Reweighting for Query Expansion,” in Proceedings of the 22nd Australasian Document Computing Symposium on - ADCS 2017, 2017, pp. 1–4.




DOI: http://dx.doi.org/10.18517/ijaseit.11.4.8868

Refbacks

  • There are currently no refbacks.



Published by INSIGHT - Indonesian Society for Knowledge and Human Development