Abstract
Web search involves user queries to process and then in response provide information. Commonly, the provided information results much irrelevant information which need to be filtered according to the user needs. Queries submitted to search engines are by nature ambiguous. The ambiguous queries constitute a significant fraction of such instances and pose real challenges to the web search. It has also created an interest for the researchers to deal with search by considering the context along with temporal perspective. Furthermore, contextual as well as temporal information retrieval has been a topic of excessive interest in recent years. The purpose is to enhance the effectiveness of retrieved information in documents and queries. This paper presents a new method PsAQCM of classifying the ambiguous queries based on the post-search results by applying content similarity approach. Java-based prototype is developed to derive the contextual and temporal information from the web results based on the 220, 44, and 114 ambiguous queries of GISQC_DS, AMBIENT and MORESQUE dataset separately. Our proposed method attained 51 %, 82 % and 78 % independently, improved results in terms of query ambiguity resolution. In future work, we intend to develop a small scale search engine which will enable us to carry out a full text analysis in order to improve the search performance in case of ambiguous queries.
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References
Zhang, H., Adviser-Jacob, E.: Query enhancement with topic detection and disambiguation for robust retrieval (2013)
Roul, R.K., Sahay, S.K.: An effective information retrieval for ambiguous query. arXiv preprint (2012). arXiv:1204.1406
Campos, R., et al.: Disambiguating implicit temporal queries by clustering top relevant dates in web snippets. In: 2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology (WI-IAT). IEEE (2012)
Drew, T., Wolfe, J.M.: Hybrid search in the temporal domain: monitoring an RSVP stream for multiple targets held in memory. J. Vis. 12(9), 1276 (2012)
Lan, R., et al.: Temporal search and replace: an interactive tool for the analysis of temporal event sequences. HCIL, University of Maryland, College Park, Maryland, Technical report HCIL-2013-TBD (2013)
Kraft, R., et al.: Searching with context. In: Proceedings of the 15th International Conference on World Wide Web. ACM (2006)
Mizzaro, S., Vassena, L.: A social approach to context-aware retrieval. World Wide Web 14(4), 377–405 (2011)
Anastasiu, D.C., et al.: A novel two-box search paradigm for query disambiguation. World Wide Web 16(1), 1–29 (2013)
Song, R., et al.: Identification of ambiguous queries in web search. Inf. Process. Manag. 45(2), 216–229 (2009)
Bunescu, R.C., Pasca, M.: Using encyclopedic knowledge for named entity disambiguation. In: EACL (2006)
Mihalcea, R., Csomai, A.: Wikify!: linking documents to encyclopedic knowledge. In: Proceedings of the Sixteenth ACM Conference on Information and Knowledge Management. ACM (2007)
Jones, R., Diaz, F.: Temporal profiles of queries. ACM Trans. Inf. Syst. (TOIS) 25(3), 14 (2007)
Salton, G., Buckley, C.: Term-weighting approaches in automatic text retrieval. Inf. process. Manag. 24(5), 513–523 (1988)
Singhal, A.: Modern information retrieval: a brief overview. IEEE Data Eng. Bull. 24(4), 35–43 (2001)
Tamine-Lechani, L., Boughanem, M., Daoud, M.: Evaluation of contextual information retrieval effectiveness: overview of issues and research. Knowl. Inf. Syst. 24(1), 1–34 (2010)
Campos, R.: Google Insights for Search Query Classification Dataset (GISQC_DS) (2011)
Carpineto, C., Romano, G.: Ambient dataset (2008). http://credo.fub.it/ambient/
Navigli, R., Crisafulli, G.: Inducing word senses to improve web search result clustering. In: Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing (EMNLP 2010). MIT Stata Center, Massachusetts (2010)
Acknowledgement
We would like to thank the Universiti Teknologi Malaysia and the Malaysia Ministry of Higher Education (MOHE) Research University Grant Scheme (Vot No. Q.J130000.2528.05H84) and also (Vot No: 4F315) for the facilities as well as support to conduct this research study. Moreover, we would also like to say thanks to the Higher Education Commission of Pakistan and the Gomal University Dera Ismail Khan, Pakistan.
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Kamal, S., Ibrahim, R., Ghani, I. (2016). Post-search Ambiguous Query Classification Method Based on Contextual and Temporal Information. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, TP. (eds) Intelligent Information and Database Systems. ACIIDS 2016. Lecture Notes in Computer Science(), vol 9622. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49390-8_56
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DOI: https://doi.org/10.1007/978-3-662-49390-8_56
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