Thijs Westerveld

The Importance of Prior Probabilities for Entry Page Search

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.

Translation Resources, Merging Strategies and Relevance Feedback for Cross-language Information Retrieval

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Experimental result analysis for a generative probabilistic image retrieval model

The main conclusion from the metrics-based evaluation of video retrieval systems at TRECs video track is that non-interactive image retrieval from general collections using visual information only is not yet feasible. We show how a detailed analysis of retrieval results -- looking beyond mean average precision (MAP) scores on topical relevance -- gives significant insight in the main problems with the visual part of the retrieval model under study. Such an analytical approach proves an important addition to standard evaluation measures.

Probabilistic multimedia retrieval

We present a framework in which probabilistic models for textual and visual information retrieval can be integrated seamlessly. The framework facilitates searching for imagery using textual descriptions and visual examples simultaneously. The underlying Language Models for text and Gaussian Mixture Models for images have proven successful in various retrieval tasks.

The INEX 2006 Multimedia Track

The multimedia track focuses on using the structure of the document to extract, relate, and combine the relevance of different multimedia fragments. This paper presents a brief overview of the track, it’s collection tasks and goals. We also report the results and the approaches of the participating groups.

Multimedia Search Without Visual Analysis: The Value of Linguistic and Contextual Information

This paper addresses the focus of this special issue by analyzing the potential contribution of linguistic content and other nonimage aspects to the processing of audiovisual data. It summarizes the various ways in which linguistic content analysis contributes to enhancing the semantic annotation of multimedia content, and, as a consequence, to improving the effectiveness of conceptual media access tools. A number of techniques are presented, including the time-alignment of textual resources, audio and speech processing, content reduction and reasoning tools, and the exploitation of surface features

TIJAH scratches INEX 2005: vague element selection, image search, overlap, and relevance feedback

Retrieving information from heterogeneous data sources in a flexible manner and within a single (database) framework is still a challenge. In this paper we present several extensions of our prototype database system TIJAH developed for structured retrieval. The extensions are aimed at modeling vague selection of XML elements and image retrieval. All three levels (conceptual, logical, and physical) of the TIJAH system are enhanced to support the extensions. Additionally, we analyze different ways of removing overlap and explain how structural information can be used for relevance feedback.

Translation Resources, Merging Strategies, and Relevance Feedback for Cross-Language Information Retrieval

This paper describes the official runs of the Twenty-One group for the first CLEF workshop. The Twenty-One group participated in the monolingual, bilingual and multilingual tasks. The following new techniques are introduced in this paper. In the bilingual task we experimented with different methods to estimate translation probabilities. In the multilingual task we experimented with refinements on raw-score merging techniques and with a new relevance feedback algorithm that re-estimates both the models translation probabilities and the relevance weights. Finally, we performed preliminary experiments to exploit the web to generate translation probabilities and bilingual dictionaries, notably for English-Italian and English-Dutch.

Structural features in content oriented XML retrieval

The structural features of XML components are an extra source of information that should be used in a content-oriented retrieval task on this type of documents. In this paper we explore one of the structural features from the INEX collection [1] that could be used in content-oriented search. We analyse the gain this knowledge could add to the performance of an information retrieval system and present a first approach on how this structural information could be extracted from a relevance feedback process to be used as priors in a language modelling framework.

Multimedia retrieval at INEX 2006

Structured document retrieval allows for the retrieval of document fragments, i.e. XML elements, containing relevant information. The main INEX Ad Hoc track focuses on text-based XML element retrieval. Although text is dominantly present in most XML document collections, other types of media can also be found. Existing research on multimedia information retrieval has shown that it is far from trivial to determine the combined relevance of a document that contains several multimedia objects. The objective of the INEX multimedia track is to exploit the XML structure that provides a logical level at which multimedia objects are connected, to improve the retrieval performance of an XML-driven multimedia information retrieval system.