Miles Efron
Gene Golovchinsky
ABSTRACT
Temporal aspects of documents can impact relevance for certain kinds of queries. In this paper, we build on earlier work of modeling temporal information. We propose an extension to the Query Likelihood Model that incorporates query-specific information to estimate rate parameters, and we introduce a temporal factor into language model smoothing and query expansion using pseudo-relevance feedback. We evaluate these extensions using a Twitter corpus and two newspaper article collections. Results suggest that, compared to prior approaches, our models are more effective at capturing the temporal variability of relevance associated with some topics.
- Adar, E. Teevan, J., Dumais, S.T., and Elsas, J.L., 2009. The web changes everything: understanding the dynamics of web content. Proceedings of the Second ACM International Conference on Web Search and Data Mining (New York, NY, USA, 2009), 282--291. Google Scholar
Digital Library
- Bernstein, M. Suh, B., Hong, L., Chen. J., Kairam, S., and Chi, E. 2010. Eddi: Interactive Topic-Based Browsing of Social Status Streams. UIST 2010: ACM Symposium on User Interface Software and Technology. (forthcoming) (2010). Google ScholarDigital Library
- Bolstad, W.M. Introduction to Bayesian Statistics. Wiley-Interscience.Google Scholar
- Dai, N. and Davison, B.D. 2010. Freshness matters. Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval - SIGIR '10 (Geneva, Switzerland, 2010), 114. Google ScholarDigital Library
- Dakka, W., Gravano, L., Ipeirotis, P., Answering General Time-Sensitive Queries, IEEE Transactions on Knowledge and Data Engineering, vol. 99, no. PrePrints, 2010. Google ScholarDigital Library
- Dong, A. Zhang, R., Kolari, P., Bai, J., Diaz, F., Chang, Y., Zheng, Z., and Zha, H. 2010. Time is of the essence: improving recency ranking using Twitter data. Proceedings of the 19th international conference on World wide web (New York, NY, USA, 2010), 331--340. Google ScholarDigital Library
- Efron, M. 2010. Hashtag retrieval in a microblogging environment. Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval (Geneva, Switzerland, 2010), 787--788. Google ScholarDigital Library
- Efron, M. and Winget, M. 2010. Questions are content: A Taxonomy of Questions in a Microblogging Environment. Proceedings of the 2010 Annual Meeting of the American Society for Information Science and Technology. (2010). Google ScholarDigital Library
- Evans, B.M. and Chi, E.H. 2008. Towards a model of understanding social search. Proceedings of the 2008 ACM conference on Computer supported cooperative work (San Diego, CA, USA, 2008), 485--494. Google ScholarDigital Library
- Golovchinsky, G. and Efron, M. 2010. Making sense of Twitter search. Proc. CHI2010 Workshop on Microblogging: What and How Can We Learn From It? April 11, 2010. (2010).Google Scholar
- Horowitz, D. and Kamvar, S.D. 2010. The anatomy of a large-scale social search engine. Proceedings of the 19th international conference on World wide web (Raleigh, North Carolina, USA, 2010), 431--440. Google ScholarDigital Library
- Jones, R. and Diaz, F. 2007. Temporal profiles of queries. ACM Transactions on Information Systems. 25, 3 (2007), 14-es. Google ScholarDigital Library
- King, I., and Li, J. 2009. Proceeding of the 2nd ACM workshop on Social web search and mining. (Hong Kong, China, 2009), 70. Google ScholarCross Ref
- Lavrenko, V. and Croft, W.B. 2001. Relevance based language models. Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval (New York, NY, USA, 2001), 120--127. Google ScholarDigital Library
- Li, X. and Croft, W.B. 2003. Time-based language models. Proceedings of the twelfth international conference on Information and knowledge management - CIKM '03 (New Orleans, LA, USA, 2003), 469. Google ScholarDigital Library
- Morris, M.R., Teevan, J., and Panovich, Katrina. 2010. What do people ask their social networks, and why?: a survey study of status message q &a behavior. Proceedings of the 28th international conference on Human factors in computing systems (Atlanta, Georgia, USA, 2010), 1739--1748. Google ScholarDigital Library
- Pickens, J. and Golovchinsky, G. 2008. Ranked feature fusion models for ad hoc retrieval. Proceeding of the 17th ACM conference on Information and knowledge management (New York, NY, USA, 2008), 893--900. Google ScholarDigital Library
- Ponte, J.M. and Croft, W.B. 1998. A language modeling approach to information retrieval. SIGIR 1998: Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval. (1998), 275--281. Google ScholarDigital Library
- Robertson, S.E. Walker, S., Jones, S., Hancock-Beaulieu, M.M., and Gatford, M. 1994. Okapi at TREC-3. In Proceedings of the Third Text REtrieval Conference (TREC 1994) (1994).Google Scholar
- Teevan, J., Dumais, S.T., and Liebling, D.J. 2010. A longitudinal study of how highlighting web content change affects people's web interactions. Proceedings of the 28th international conference on Human factors in computing systems - CHI '10 (Atlanta, Georgia, USA, 2010), 1353. Google ScholarDigital Library
- Twitter. http://twitter.com. Accessed: 12-02--2010.Google Scholar
- Voorhees, E.M. 2007. TREC: Continuing information retrieval's tradition of experimentation. Commun. ACM. 50, (Nov. 2007), 51--54. Google ScholarDigital Library
- Yang, J. and Leskovec, J. 2011. Temporal variation in online media. ACM Internation Conference on Web Search and Data Mining (WSDM '11) (2011). Google ScholarDigital Library
- Zhai, C. and Lafferty, J. 2001. Model-based feedback in the language modeling approach to information retrieval. CIKM 2001: Proceedings of the tenth international conference on Information and knowledge management. (2001), 403--410. Google ScholarDigital Library
- Zhai, C. and Lafferty, J. 2004. A Study of Smoothing Methods for Language Models Applied to Information Retrieval. ACM Transactions on Information Systems. 2, 2 (2004), 179--214. Google ScholarDigital Library
- Zhai, C. 2008. Statistical Language Models for Information Retrieval A Critical Review. Found. Trends Inf. Retr. 2, (Mar. 2008), 137--213. Google ScholarDigital Library
Index Terms
- Estimation methods for ranking recent information
Recommendations
Improving retrieval of short texts through document expansion
SIGIR '12: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrievalCollections containing a large number of short documents are becoming increasingly common. As these collections grow in number and size, providing effective retrieval of brief texts presents a significant research problem. We propose a novel approach to ...
When time meets information retrieval
With the advent of Web search and the large amount of data published on the Web sphere, a tremendous amount of documents become strongly time-dependent. In this respect, the time dimension has been extensively exploited as a highly important relevance ...
Scalable Content-Based Ranking in P2P Information Retrieval
KES '08: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part INumerous retrieval models have been defined within the field of information retrieval (IR) to produce a ranked and ordered list of documents relevant to a given query. Existing models are in general well-explored and thoroughly evaluated using ...
Comments