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This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in roceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval, http://dx.doi.org/10.1145/2009916.2010097 ; Diversification and personalization methods are common ap-proaches to deal with the one-size-fits-all paradigm of Web search engines. We performed a user study with 190 subjects where we analyzed the effects of diversification and personalization methods in a Web search engine. The obtained results suggest that our proposed combination of diversification and personalization factors may be a way to overcome the notion of intrusiveness in personalized approaches. ; This work is supported by the Spanish Government (TIN2008-06566-C04-02), and the Government of Madrid (S2009TIC-1542).

This is an electronic version of the paper presented at the International Workshop on Diversity in Document Retrieval (DDR 2012), held in Seattle on 2012 ; Recent developments in Information Retrieval diversity are based on the consideration of a space of information need aspects, a notion which takes different forms in the literature. The choice of a suitable aspect space for diversification is a critical issue when designing an IR diversification strategy, which has not been explicitly addressed to some depth in the literature. This paper aims to identify relevant properties of the aspect space which may help the system designer in making a suitable choice in selecting and configuring this space, and diagnosing malfunctions of the diversification algorithms. In particular, we identify the mutual information between aspects and documents as a meaningful magnitude, in terms of which anomalous cases can be characterized. We further seek to discern favorable cases through a combination of theoretic and empirical analysis. ; This work is supported by the Spanish Government (TIN2011-28538-C02-01), and the Government of Madrid (S2009TIC-1542).

This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval, http://dx.doi.org/10.1145/2009916.2010124. ; Diversity as a relevant dimension of retrieval quality is receiving increasing attention in the Information Retrieval and Recommender Systems (RS) fields. The problem has nonetheless been approached under different views and formulations in IR and RS respectively, giving rise to different models, methodologies, and metrics, with little convergence between both fields. In this poster we explore the adaptation of diversity metrics, techniques, and principles from ad-hoc IR to the recommendation task, by introducing the notion of user profile aspect as an analogue of query intent. As a particular approach, user aspects are automatically extracted from latent item features. Empirical results support the proposed approach and provide further insights. ; This work is supported by the Spanish Government (TIN2008- 06566-C04-02), and the Government of Madrid (S2009TIC-1542).

This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval, http://dx.doi.org/10.1145/1835449.1835636 ; In this paper, we present a folksonomy-based approach for implicit user intent extraction during a Web search process. We present a number of result re-ranking techniques based on this representation that can be applied to any Web search engine. We perform a user experiment the results of which indicate that this type of representation is better at context extraction than using the actual textual content of the document. ; This research was partially supported by the Spanish Ministry of Science and Education (TIN2008-06566-C04-02) and the Regional Government of Madrid (S2009TIC-1542).

This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM Transactions on Information Systems, http://dx.doi.org/10.1145/1961209.1961214 ; We present a model for exploiting community-based usage information for video retrieval, where implicit usage information from past users is exploited in order to provide enhanced assistance in video retrieval tasks, and alleviate the effects of the semantic gap problem. We propose a graph-based model for all types of implicit and explicit feedback, in which the relevant usage information is represented. Our model is designed to capture the complex interactions of a user with an interactive video retrieval system, including the representation of sequences of user-system interaction during a search session. Building upon this model, four recommendation strategies are defined and evaluated. An evaluation strategy is proposed based on simulated user actions, which enables the evaluation of our recommendation strategies over a usage information pool obtained from 24 users performing four different TRECVid tasks. Furthermore, the proposed simulation approach is used to simulate usage information pools with different characteristics, with which the recommendation approaches are further evaluated on a larger set of tasks, and their performance is studied with respect to the scalability and quality of the available implicit information. ; This work was partially supported by the Spanish Ministry of Science and Education (TIN2008-06566-C04-02) and the Regional Government of Madrid (S2009TIC-1542). F. Hopfgartner was supported by a postdoctoral fellowship of the German Academic Exchange Service (DAAD)