Abstract
Temporal information retrieval exploits temporal features of document collections and queries. Temporal document priors are used to adjust the score of a document based on its publication time. We consider a class of temporal document priors that is inspired by retention functions considered in cognitive psychology that are used to model the decay of memory. Many such functions used as a temporal document prior have a positive effect on overall retrieval performance. We examine the stability of this effect across news and microblog collections and discover interesting differences between retention functions. We also study the problem of optimizing parameters of the retention functions as temporal document priors; some retention functions display consistent good performance across large regions of the parameter space. A retention function based on a Weibull distribution is the preferred choice for a temporal document prior.
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References
Porter, S., Birt, A.R.: Is traumatic memory special? Appl. Cogn. Psych. 15, 101–117 (2001)
Meeter, M., Murre, J.M.J., Janssen, S.M.J.: Remembering the news: modeling retention data from a study with 14,000 participants. Memory & Cognition 33, 793–810 (2005)
Hertwig, R., et al.: Fluency heuristic: a model of how the mind exploits a by-product of information retrieval. J. Exp. Psych.: Learning, Memory, and Cogn. 34, 1191–1206 (2008)
Chessa, A.G., Murre, J.M.: A memory model for internet hits after media exposure. Physica A Statistical Mechanics and its Applications (2004)
Chessa, A.G., Murre, J.M.: Modelling memory processes and internet response times: Weibull or power-law? Physica A Statistical Mechanics and its Applications (2006)
Li, X., Croft, W.B.: Time-Based Language Models. In: CIKM 2003 (2003)
Massoudi, K., Tsagkias, M., de Rijke, M., Weerkamp, W.: Incorporating Query Expansion and Quality Indicators in Searching Microblog Posts. In: Clough, P., Foley, C., Gurrin, C., Jones, G.J.F., Kraaij, W., Lee, H., Mudoch, V. (eds.) ECIR 2011. LNCS, vol. 6611, pp. 362–367. Springer, Heidelberg (2011)
Efron, M., Organisciak, P., Fenlon, K.: Improving retrieval of short texts through document expansion. In: SIGIR 2012 (2012)
Efron, M., Golovchinsky, G.: Estimation Methods for Ranking Recent Information. In: SIGIR 2011 (2011)
Ebbinghaus, H.: Memory: a contribution to experimental psychology. Teachers College, Columbia University (1913)
Schooler, L.J., Anderson, J.R.: The role of process in the rational analysis of memory. Cognitive Psychology 32, 219–250 (1997)
Rubin, D.C., Hinton, S., Wenzel, A.: The precise time course of retention. Journal of Experimental Psychology: Learning, Memory, and Cognition 25, 1161–1176 (1999)
Wickens, T.D.: Measuring the time course of retention. On human memory: Evolution, progress, and reflections on the 30th anniversary of the Atkinson–Shiffrin model (1999)
Heathcote, A., Brown, S., Mewhort, D.J.: The power law repealed: the case for an exponential law of practice. Psychonomic Bulletin & Review 7, 185–207 (2000)
Alonso, O., Strötgen, J., Baeza-Yates, R., Gertz, M.: Temporal Information Retrieval: Challenges and Opportunities. In: TWAW 2011, pp. 1–8 (2011)
Verhagen, M., Pustejovsky, J.: Temporal processing with the TARSQI toolkit. In: COLING 2008 (2008)
Odijk, D., de Rooij, O., Peetz, M.-H., Pieters, T., de Rijke, M., Snelders, S.: Semantic Document Selection. In: Zaphiris, P., Buchanan, G., Rasmussen, E., Loizides, F. (eds.) TPDL 2012. LNCS, vol. 7489, pp. 215–221. Springer, Heidelberg (2012)
Keikha, M., Gerani, S., Crestani, F.: Time-based relevance models. In: SIGIR 2011 (2011)
Amodeo, G., Amati, G., Gambosi, G.: On relevance, time and query expansion. In: CIKM 2011. ACM (2011)
Dakka, W., Gravano, L., Ipeirotis, P.G.: Answering General Time Sensitive Queries. In: CIKM 2008, pp. 1437–1438 (2008)
Peetz, M.-H., Meij, E., de Rijke, M., Weerkamp, W.: Adaptive Temporal Query Modeling. In: Baeza-Yates, R., de Vries, A.P., Zaragoza, H., Cambazoglu, B.B., Murdock, V., Lempel, R., Silvestri, F. (eds.) ECIR 2012. LNCS, vol. 7224, pp. 455–458. Springer, Heidelberg (2012)
Efron, M.: Query-specific recency ranking. In: SIGIR 2012 Workshop on Time-aware Information Access (2012)
Ponte, J.M., Croft, W.B.: A language modeling approach to information retrieval. In: SIGIR 1998 (1998)
Manning, C.D., Raghavan, P., Schütze, H.: Introduction to Information Retrieval. Cambridge University Press, New York (2008)
Ainslie, G., Haslam, N.: Hyperbolic discounting. In: Choice over time. Russell Sage Foundation (1992)
Amati, G., et al.: FUB, IASI-CNR, UNIVAQ at TREC 2011. In: TREC 2011, NIST (2011)
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Peetz, MH., de Rijke, M. (2013). Cognitive Temporal Document Priors. In: Serdyukov, P., et al. Advances in Information Retrieval. ECIR 2013. Lecture Notes in Computer Science, vol 7814. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36973-5_27
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DOI: https://doi.org/10.1007/978-3-642-36973-5_27
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