Please wait a minute...
New Technology of Library and Information Service  2016, Vol. 32 Issue (11): 34-43    DOI: 10.11925/infotech.1003-3513.2016.11.05
Orginal Article Current Issue | Archive | Adv Search |
The Impacts of Query Specificity on Information Retrieval
Ren Ke1,Lu Wei1,2(),Ding Heng1
1School of Information Management, Wuhan University, Wuhan 430072, China
2Center for the Study of Information Resources, Wuhan University, Wuhan 430072, China
Download:
Export: BibTeX | EndNote (RIS)      
Abstract  

[Objective] This paper analyzes the impacts of query specificity on the effectiveness of information retrieval systems, aiming to improve the performance of search engine and user experience. [Methods] First, we manually constructed a labeling set for queries from the TREC Web Track. Second, we adopted the Dirichlet language model, linear interpolation language model and BM25 model to examine each query’s performance. Finally, we used the average information retrieval evaluation index as the benchmark to explore the impacts of query specificity. [Results] For the highest-ranked results, the queries with narrower specificity had better retrieval performance than their boarder counterparts. [Limitations] The proposed method was only examined with data provided by TREC. More studies were needed to evaluate its performance with other data sets. [Conclusions] Search engines should focus on the precision of the highest ranked results, and then modify their retrieval model accordingly.

Key wordsQuery intention      Query specificity      Retrieval result     
Received: 18 July 2016      Published: 20 December 2016

Cite this article:

Ren Ke,Lu Wei,Ding Heng. The Impacts of Query Specificity on Information Retrieval. New Technology of Library and Information Service, 2016, 32(11): 34-43.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2016.11.05     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2016/V32/I11/34

[1] 王娜, 陈会敏. 泛在网络中信息过载危害及原因的调查分析[J]. 情报理论与实践, 2014, 37(11): 20-25.
[1] (Wang Na, Chen Huimin.Investigation on the Harm and Cause of Information Overload in Ubiquitous Network[J]. Information Studies: Theory & Application, 2014, 37(11): 20-25.)
[2] Jones K S.A Statistical Interpretation of Term Specificity and Its Application in Retrieval[J]. Journal of Documentation, 1972, 28(1): 11-21.
[3] Kim G.Relationship Between Index Term Specificity and Relevance Judgment[J]. Information Processing & Management, 2006, 42(5): 1218-1229.
[4] 唐祥彬, 陆伟, 张晓娟, 等. 查询专指度特征分析与自动识别[J]. 现代图书情报技术, 2015(2): 15-23.
[4] (Tang Xiangbin, Lu Wei, Zhang Xiaojuan, et al.Feature Analysis and Automatic Identification of Query Specificity[J]. New Technology of Library and Information Service, 2015(2): 15-23.)
[5] 宋巍. 基于主题的查询意图识别研究[D].哈尔滨: 哈尔滨工业大学, 2013.
[5] (Song Wei.Research on Topic Based Query Intent Identification [D]. Harbin: Harbin Institute of Technology, 2013.)
[6] Broder A.A Taxonomy of Web Search[J]. ACM SIGIR Forum, 2002, 36(2): 3-10.
[7] Rose D E, Levinson D.Understanding User Goals in Web Search [C]. In: Proceedings of the 13th International Conference on World Wide Web. New York, NY, USA: ACM, 2004: 13-19.
[8] Baeza-Yates R, Calderón-Benavides L, González-Caro C.The Intention Behind Web Queries [C]. In: Proceedings of the 13th International Conference on String Processing and Information Retrieval. Berlin, Heidelberg: Springer-Verlag, 2006: 98-109.
[9] González-Caro C, Calderón-Benavides L, Baeza-Yates R, et al.Web Queries: The Tip of the Iceberg of the User’s Intent [C]. In: Proceedings of the 4th ACM WSDM Conference, Hong Kong, China. 2011.
[10] Hafernik C T.The Relationship Between Query Length, Parts of Speech Usage and Web Search Query Specificity [D]. The Pennsylvania State University, 2013.
[11] Tamine L, Chouquet C, Palmer T.Analysis of Biomedical and Health Queries: Lessons Learned from TREC and CLEF Evaluation Benchmarks[J]. Journal of the Association for Information Science and Technology, 2015, 66(12): 2626-2642.
[12] Phan N, Bailey P, Wilkinson R.Understanding the Relationship of Information Need Specificity to Search Query Length [C]. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR’07). New York: ACM, 2007: 709-710.
[13] Mu X, Lu K.Improving UMLS Metathesaurus Query Expansion Based on the Query Specificity and Length [C]. In: Proceedings of the ACM SIGKDD Workshop on Health Informatics.2012.
[14] Heine M H.An Investigation of the Relative Influences of Database Informativeness, Query Size and Query Term Specificity on the Effectiveness of Medline Searching[J]. Journal of Information Science, 1995, 21(3): 173-185.
[15] Ingwersen P, Jarvelin K.The Turn: Integration of Information Seeking and Retrieval in Context[M]. Springer, 2005.
[16] Ramírez G, de Vries A P. Relevant Contextual Features in XML Retrieval [C]. In: Proceedings of the 1st International Conference on Information Interaction in Context. New York: ACM, 2006: 56-65.
[17] Carletta J.Assessing Agreement on Classification Tasks: The Kappa Statistic[J]. Computational Linguistics, 1996, 22(2): 249-254.
[18] Siegel S, Castellan N J.Non-parametric Statistics for the Behavioral Sciences[J]. American Catholic Sociological Review, 1957, 18(2). DOI: 10.2307/3708383.
[19] Ponte J M, Croft W B.A Language Modeling Approach to Information Retrieval [C]. In: Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 1998: 275-281.
[20] Robertson S E, Jones K S.Relevance Weighting of Search Terms[J]. Journal of the American Society for Information Science, 1976, 27(3): 129-146.
[1] Tang Xiangbin, Lu Wei, Zhang Xiaojuan, Huang Shihao. Feature Analysis and Automatic Identification of Query Specificity[J]. 现代图书情报技术, 2015, 31(2): 15-23.
[2] Zhou Jingyi,Sun Tan. Application of Information Visualization in Digital Library[J]. 现代图书情报技术, 2005, 21(1): 5-8.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn