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Hugo Zaragoza

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Hugo Zaragoza

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Publications by Hugo Zaragoza (bibliography)

» 2008 «

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Vallet, David and Zaragoza, Hugo (2008): Inferring the most important types of a query: a semantic approach. In: Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2008. pp. 857-858. Available online

“In this paper we present a technique for ranking the most important types or categories for a given query. Rather than trying to find the category of the query, known as query categorization, our approach seeks to find the most important types related to the query results. Not necessarily the query category falls into this ranking of types and therefore our approach can be complementary.”

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» 2007 «

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Najork, Marc A., Zaragoza, Hugo and Taylor, Michael J. (2007): Hits on the web: how does it compare?. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2007. pp. 471-478. Available online

“This paper describes a large-scale evaluation of the effectiveness of HITS in comparison with other link-based ranking algorithms, when used in combination with a state-of-the-art text retrieval algorithm exploiting anchor text. We quantified their effectiveness using three common performance measures: the mean reciprocal rank, the mean average precision, and the normalized discounted cumulative gain measurements. The evaluation is based on two large data sets: a breadth-first search crawl of 463 million web pages containing 17.6 billion hyperlinks and referencing 2.9 billion distinct URLs; and a set of 28,043 queries sampled from a query log, each query having on average 2,383 results, about 17 of which were labeled by judges. We found that HITS outperforms PageRank, but is about as effective as web-page in-degree. The same holds true when any of the link-based features are combined with the text retrieval algorithm. Finally, we studied the relationship between query specificity and the effectiveness of selected features, and found that link-based features perform better for general queries, whereas BM25F performs better for specific queries.”

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Piwowarski, Benjamin and Zaragoza, Hugo (2007): Predictive user click models based on click-through history. In: Silva, Mario J., Laender, Alberto H. F., Baeza-Yates, Ricardo A., McGuinness, Deborah L., Olstad, Bjørn, Olsen, Øystein Haug and Falcão, André O. (eds.) Proceedings of the Sixteenth ACM Conference on Information and Knowledge Management - CIKM 2007 November 6-10, 2007, Lisbon, Portugal. pp. 175-182. Available online

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Zaragoza, Hugo, Rode, Henning, Mika, Peter, Atserias, Jordi, Ciaramita, Massimiliano and Attardi, Giuseppe (2007): Ranking very many typed entities on wikipedia. In: Silva, Mario J., Laender, Alberto H. F., Baeza-Yates, Ricardo A., McGuinness, Deborah L., Olstad, Bjørn, Olsen, Øystein Haug and Falcão, André O. (eds.) Proceedings of the Sixteenth ACM Conference on Information and Knowledge Management - CIKM 2007 November 6-10, 2007, Lisbon, Portugal. pp. 1015-1018. Available online

» 2006 «

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Taylor, Michael J., Zaragoza, Hugo, Craswell, Nick, Robertson, Stephen and Burges, Chris (2006): Optimisation methods for ranking functions with multiple parameters. In: Yu, Philip S., Tsotras, Vassilis J., Fox, Edward A. and Liu, Bing (eds.) Proceedings of the 2006 ACM CIKM International Conference on Information and Knowledge Management November 6-11, 2006, Arlington, Virginia, USA. pp. 585-593. Available online

» 2005 «

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Craswell, Nick, Robertson, Stephen, Zaragoza, Hugo and Taylor, Michael (2005): Relevance weighting for query independent evidence. In: Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2005. pp. 416-423. Available online

“A query independent feature, relating perhaps to document content, linkage or usage, can be transformed into a static, per-document relevance weight for use in ranking. The challenge is to find a good function to transform feature values into relevance scores. This paper presents FLOE, a simple density analysis method for modelling the shape of the transformation required, based on training data and without assuming independence between feature and baseline. For a new query independent feature, it addresses the questions: is it required for ranking, what sort of transformation is appropriate and, after adding it, how successful was the chosen transformation? Based on this we apply sigmoid transformations to PageRank, indegree, URL Length and ClickDistance, tested in combination with a BM25 baseline.”

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» 2004 «

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Hiemstra, Djoerd, Robertson, Stephen and Zaragoza, Hugo (2004): Parsimonious language models for information retrieval. In: Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2004. pp. 178-185. Available online

“We systematically investigate a new approach to estimating the parameters of language models for information retrieval, called parsimonious language models. Parsimonious language models explicitly address the relation between levels of language models that are typically used for smoothing. As such, they need fewer (non-zero) parameters to describe the data. We apply parsimonious models at three stages of the retrieval process: 1) at indexing time; 2) at search time; 3) at feedback time. Experimental results show that we are able to build models that are significantly smaller than standard models, but that still perform at least as well as the standard approaches.”

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Robertson, Stephen E., Zaragoza, Hugo and Taylor, Michael J. (2004): Simple BM25 extension to multiple weighted fields. In: Grossman, David A., Gravano, Luis, Zhai, Chengxiang, Herzog, Otthein and Evans, David A. (eds.) Proceedings of the 2004 ACM CIKM International Conference on Information and Knowledge Management November 8-13, 2004, Washington, DC, USA. pp. 42-49. Available online

» 2003 «

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Zaragoza, Hugo, Hiemstra, Djoerd and Tipping, Michael (2003): Bayesian extension to the language model for ad hoc information retrieval. In: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2003. pp. 4-9. Available online

“We propose a Bayesian extension to the ad-hoc Language Model. Many smoothed estimators used for the multinomial query model in ad-hoc Language Models (including Laplace and Bayes-smoothing) are approximations to the Bayesian predictive distribution. In this paper we derive the full predictive distribution in a form amenable to implementation by classical IR models, and then compare it to other currently used estimators. In our experiments the proposed model outperforms Bayes-smoothing, and its combination with linear interpolation smoothing outperforms all other estimators.”

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Changes to this page (author)

20 Feb 2010: Enabled abstracts to be shown on Hugo Zaragoza's author page.
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24 Jun 2007: Author was added to the bibliography

Publication statistics

Publication period:2003-2008
Publication count:9
Number of co-authors:16

Productive colleagues

Hugo Zaragoza's 3 most productive colleagues in number of publications:

Stephen Robertson:16
Djoerd Hiemstra:14
Nick Craswell:13

Collaboration count

Number of publications with 3 favourite co-authors:

Michael J. Taylor:3
Stephen Robertson:3
Djoerd Hiemstra:2

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Learn more about Hugo Zaragoza:
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Conference Calendar

Mar 22

Workshop on Pervasive healthcare in the home : Supporting patient motivation and engagement

Mar 22

UX People

Mar 22

ETRA '10 - Eye Tracking Research & Applications Symp.

Mar 21

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Hugo Zaragoza

Publications by Hugo Zaragoza (bibliography)

» 2008 «

» 2007 «

» 2006 «

» 2005 «

» 2004 «

» 2003 «

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Changes to this page (author)

Publication statistics

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Conference Calendar

Eva Hornecker on Tangible Interaction

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