Djoerd Hiemstra

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Publications by Djoerd Hiemstra (bibliography)

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» 2008 «

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Kaptein, Rianne, LI, Rongmei, Hiemstra, Djoerd and Kamps, Jaap (2008): Using parsimonious language models on web data. In: Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2008. pp. 763-764. Available online

In this paper we explore the use of parsimonious language models for web retrieval. These models are smaller thus more efficient than the standard language models and are therefore well suited for large-scale web retrieval. We have conducted experiments on four TREC topic sets, and found that the parsimonious language model results in improvement of retrieval effectiveness over the standard language model for all data-sets and measures. In all cases the improvement is significant, and more substantial than in earlier experiments on newspaper/newswire data.

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Serdyukov, Pavel, Rode, Henning and Hiemstra, Djoerd (2008): Exploiting sequential dependencies for expert finding. In: Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2008. pp. 795-796. Available online

We propose an expert finding method based on assumption of sequential dependence between a candidate expert and the query terms in the scope of a document. We assume that the strength of relation of a candidate to the document's content depends on its position in this document with respect to the positions of the query terms. The experiments on the official Enterprise TREC data demonstrate the advantage of our method over the method based on independence of query terms and persons in a document.

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Serdyukov, Pavel, Rode, Henning and Hiemstra, Djoerd (2008): Modeling expert finding as an absorbing random walk. In: Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2008. pp. 797-798. Available online

We introduce a novel approach to expert finding based on multi-step relevance propagation from documents to related candidates. Relevance propagation is modeled with an absorbing random walk. The evaluation on the two official Enterprise TREC data sets demonstrates the advantage of our method over the state-of-the-art method based on one-step propagation.

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Rode, Henning, Serdyukov, Pavel and Hiemstra, Djoerd (2008): Combining document- and paragraph-based entity ranking. In: Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2008. pp. 851-852. Available online

We study entity ranking on the INEX entity track and propose a simple graph-based ranking approach that enables to combine scores on document and paragraph level. The combined approach improves the retrieval results not only on the INEX testset, but similarly on TREC's expert finding task.

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Hauff, Claudia, Hiemstra, Djoerd and Jong, Franciska de (2008): A survey of pre-retrieval query performance predictors. In: Shanahan, James G., Amer-Yahia, Sihem, Manolescu, Ioana, Zhang, Yi, Evans, David A., Kolcz, Aleksander, Choi, Key-Sun and Chowdhury, Abdur (eds.) Proceedings of the 17th ACM Conference on Information and Knowledge Management - CIKM 2008 October 26-30, 2008, Napa Valley, California, USA. pp. 1419-1420. Available online

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Serdyukov, Pavel, Rode, Henning and Hiemstra, Djoerd (2008): Modeling multi-step relevance propagation for expert finding. In: Shanahan, James G., Amer-Yahia, Sihem, Manolescu, Ioana, Zhang, Yi, Evans, David A., Kolcz, Aleksander, Choi, Key-Sun and Chowdhury, Abdur (eds.) Proceedings of the 17th ACM Conference on Information and Knowledge Management - CIKM 2008 October 26-30, 2008, Napa Valley, California, USA. pp. 1133-1142. Available online

» 2007 «

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Serdyukov, Pavel, Hiemstra, Djoerd, Fokkinga, Maarten and Apers, Peter M. G. (2007): Generative modeling of persons and documents for expert search. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2007. pp. 827-828. Available online

In this paper we address the task of automatically finding an expert within the organization, known as the expert search problem. We present the theoretically-based probabilistic algorithm which models retrieved documents as mixtures of expert candidate language models. Experiments show that our approach outperforms existing theoretically sound solutions.

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» 2006 «

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Blok, Henk Ernst, Mihajlovic, Vojkan, Ramirez, Georgina, Westerveld, Thijs, Hiemstra, Djoerd and Vries, Arjen P. de (2006): The TIJAH XML information retrieval system. In: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2006. p. 725. Available online

» 2005 «

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Mihajlovic, Vojkan, Blok, Henk Ernst, Hiemstra, Djoerd and Apers, Peter M. G. (2005): Score region algebra: building a transparent XML-R database. In: Herzog, Otthein, Schek, Hans-Jörg and Fuhr, Norbert (eds.) Proceedings of the 2005 ACM CIKM International Conference on Information and Knowledge Management October 31 - November 5, 2005, Bremen, Germany. pp. 12-19. Available online

» 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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» 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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» 2002 «

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Kraaij, Wessel, Westerveld, Thijs and Hiemstra, Djoerd (2002): The Importance of Prior Probabilities for Entry Page Search. In: Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2002. pp. 27-34. Available online

An important class of searches on the world-wide-web has the goal to find an entry page (homepage) of an organisation. Entry page search is quite different from Ad Hoc search. Indeed a plain Ad Hoc system performs disappointingly. We explored three non-content features of web pages: page length, number of incoming links and URL form. Especially the URL form proved to be a good predictor. Using URL form priors we found over 70% of all entry pages at rank 1, and up to 89% in the top 10. Non-content features can easily be embedded in a language model framework as a prior probability.

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Hiemstra, Djoerd (2002): Term-specific smoothing for the language modeling approach to information retrieval: the importance of a query term. In: Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2002. pp. 35-41. Available online

This paper follows a formal approach to information retrieval based on statistical language models. By introducing some simple reformulations of the basic language modeling approach we introduce the notion of importance of a query term. The importance of a query term is an unknown parameter that explicitly models which of the query terms are generated from the relevant documents (the important terms), and which are not (the unimportant terms). The new language modeling approach is shown to explain a number of practical facts of today's information retrieval systems that are not very well explained by the current state of information retrieval theory, including stop words, mandatory terms, coordination level ranking and retrieval using phrases.

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» 2001 «

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Blok, Henk Ernst, Hiemstra, Djoerd, Choenni, Sunil, Jong, Franciska de, Blanken, Henk M. and Apers, Peter M. G. (2001): Predicting the Cost-Quality Trade-Off for Information Retrieval Queries: Facilitating Database Design and Query Optimization. In: Proceedings of the 2001 ACM CIKM International Conference on Information and Knowledge Management November 5-10, 2001, Atlanta, Georgia, USA. pp. 207-214. Available online

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21 Feb 2010: Enabled abstracts to be shown on Djoerd Hiemstra's author page.
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Publication statistics

Publication period:2001-2008
Publication count:14
Number of co-authors:20



Productive colleagues

Djoerd Hiemstra's 3 most productive colleagues in number of publications:

Stephen Robertson:16
Arjen P. de Vries:11
Jaap Kamps:11


Collaboration count

Number of publications with 3 favourite co-authors:

Pavel Serdyukov:5
Henning Rode:4
Henk Ernst Blok:3

 

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