Abstract
We propose a generic diversity and two novel spatial diversity algorithms for (image) search result diversification. The outputs of the algorithms are compared with the standard search results (which contains no diversity implementation) and found to be promising. In particular, the geometric mean spatial diversity algorithm manages to achieve good geographical diversity while not significantly reducing precision. To the best of our knowledge, such a quantitive evaluation of spatial diversity algorithms for context based image retrieval is new to the community.
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Chen, H., Karger, D.R.: Less is More: Probabilistic Models for Retrieving Fewer Relevant Documents. In: SIGIR 2006, pp. 429–436 (2006)
Artiles, J., Gonzalo, J., Sekine, S.: The SemEval-2007 WePS Evaluation: Establishing a Benchmark for the Web People Search Task. In: Proceedings of the Fourth International Workshop on Semantic Evaluations, Prague, Czech Republic, pp. 64–69 (June 2007)
Zhai, C.X., Cohen, W.W., Lafferty, J.: Beyond Independent Relevance: Methods and Evaluation Metrics for Subtopic Retrieval. In: SIGIR 2006, Toronto, Canada, pp. 10–17 (2003)
Carbonell, J.G., Goldstein, J.: The Use of MMR, Diversity-based Reranking for Reordering Documents and Producing Summaries. In: SIGIR 1998, Melbourne, Australia, pp. 335–336. ACM, New York (1998)
Clough, P., Joho, H., Purves, R.: Judging the Spatial Relevance of Documents for GIR. In: Lalmas, M., MacFarlane, A., Rüger, S.M., Tombros, A., Tsikrika, T., Yavlinsky, A. (eds.) ECIR 2006. LNCS, vol. 3936, pp. 548–552. Springer, Heidelberg (2006)
Purves, R.S., Clough, P., Jones, C.B., Arampatzis, A., Bucher, B., Finch, D., Fu, G., Joho, H., Syed, A.K., Vaid, S., Yang, B.: The Design and Implementation of Spirit: a Spatially Aware Search Engine for Information Retrieval on the Internet. International Journal of Geographical Information Science 21(7), 717–745 (2007)
van Kreveld, M., Reinbacher, I., Arampatzis, A., van Zwol, R.: Distributed Ranking Methods for Geographic Information Retrieval. In: Proceedings of the 20th European Workshop on Computational Geometry, pp. 231–243 (2004)
Smyth, B., McClave, P.: Similarity vs. Diversity. In: Aha, D.W., Watson, I. (eds.) ICCBR 2001. LNCS, vol. 2080, pp. 347–361. Springer, Heidelberg (2001)
Arni, T., Tang, J., Sanderson, M., Clough, P.: Creating a Test Collection to Evaluate Diversity in Image Retrieval. In: Proceedings of the Workshop on Beyond Binary Relevance: Preferences, Diversity, and Set-Level Judgments, held at SIGIR (2008)
Robertson, S.: On GMAP: and Other Transformations. In: Conference on Information and Knowledge Management, Virginia, USA, pp. 78–83 (2006)
Rattenbury, T., Good, N., Naaman, M.: Towards Automatic Extraction of Event and Place Semantics From Flickr Tags. In: Proceedings of SIGIR, pp. 103–110 (2007)
Naaman, M., Paepcke, A., Garcia-Molina, H.: From where to what: Metadata sharing for digital photographs with geographic coordinates. In: Meersman, R., Tari, Z., Schmidt, D.C. (eds.) CoopIS 2003, DOA 2003, and ODBASE 2003. LNCS, vol. 2888, pp. 196–217. Springer, Heidelberg (2003)
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Paramita, M.L., Tang, J., Sanderson, M. (2009). Generic and Spatial Approaches to Image Search Results Diversification. In: Boughanem, M., Berrut, C., Mothe, J., Soule-Dupuy, C. (eds) Advances in Information Retrieval. ECIR 2009. Lecture Notes in Computer Science, vol 5478. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00958-7_56
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DOI: https://doi.org/10.1007/978-3-642-00958-7_56
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