Catálogo de publicaciones - libros

We present a statistical approach for parsing football video structures. Based on video production conventions, a new generic structure called ‘attack’ is identified, which is an equivalent of scene in other video domains. We define four video segments to construct it, namely and . Two middle level visual features, and , are also computed. The detection process includes a two-pass classifier, a combination of Gaussian Mixture Model and Hidden Markov Models. A general suffix tree is introduced to identify and organize ‘attack’. In experiments, video structure classification accuracy of about 86% is achieved on broadcasting World Cup 2002 video data.

We have applied the concept of fractional distance measures, proposed by Aggarwal et al. [1], to content-based image retrieval. Our experiments show that retrieval performances of these measures consistently outperform the more usual Manhattan and Euclidean distance metrics when used with a wide range of high-dimensional visual features. We used the parameters learnt from a Corel dataset on a variety of different collections, including the TRECVID 2003 and ImageCLEF 2004 datasets. We found that the specific optimum parameters varied but the general performance increase was consistent across all 3 collections. To squeeze the last bit of performance out of a system it would be necessary to train a distance measure for a specific collection. However, a fractional distance measure with parameter = 0.5 will consistently outperform both and norms.

The growing need for ‘intelligent’ image retrieval systems leads to new architectures combining visual semantics and signal features that rely on highly expressive frameworks while providing fully-automated indexing and retrieval processes. Indeed, addressing the issue of integrating the two main approaches in the image indexing and retrieval literature (i.e. signal and semantic) is a viable solution for achieving significant retrieval quality. This paper presents a multi-facetted framework featuring visual semantics and signal texture descriptions for automatic image retrieval. It relies on an expressive representation formalism handling high-level image descriptions and a full-text query framework in an attempt to operate image indexing and retrieval operations beyond trivial low-level processes and loosely-coupled state-of-the-art systems. At the experimental level, we evaluate the retrieval performance of our system through recall and precision indicators on a test collection of 2500 photographs used in several world-class publications.

The performance of web search engines may often deteriorate due to the diversity and noise contained within web pages. Some methods proposed to use clickthrough data to achieve more accurate information for web pages as well as improve the search performance. However, sparseness became the great challenge in exploiting clickthrough data. In this paper, we propose a novel algorithm to exploit the user clickthrough data. It first explores the relationship between queries and web pages to mine out co-visiting as the associative relationship among the Web pages, and then Spreading Activation mechanism is used to re-rank the results of Web search. Our approach could alleviate such sparseness and the experimental results on a large set of MSN clickthrough log data show a significant improvement on search performance over the DirectHit algorithm as well as the baseline search engine.

Tools that allow effective information organisation, access and navigation are becoming increasingly important on the Web. Similarity between web pages is a concept that is central to such tools. In this paper, we examine the effect that content and layout-related aspects of web pages have on web page similarity. We consider the textual content contained within common HTML tags, the structural layout of pages, and the query terms contained within pages. Our study shows that combinations of factors can yield more promising results than individual factors, and that different aspects of web pages affect similarities between pages in a different manner. We found a number of factors that, when taken into account, can result in effective measures of similarity between web pages. Query information in particular, proved to be important for the effective organisation of web pages.

We explore the use of phrase and proximity terms in the context of web retrieval, which is different from traditional ad-hoc retrieval both in document structure and in query characteristics. We show that for this type of task, the usage of both phrase and proximity terms is highly beneficial for early precision as well as for overall retrieval effectiveness. We also analyze why phrase and proximity terms are far more effective for web retrieval than for ad-hoc retrieval.

Terrier is a modular platform for the rapid development of large-scale Information Retrieval (IR) applications. It can index various document collections, including TREC and Web collections. Terrier also offers a range of document weighting and query expansion models, based on the Divergence From Randomness framework. It has been successfully used for ad-hoc retrieval, cross-language retrieval, Web IR and intranet search, in a centralised or distributed setting.

In this poster we describe the development of a distributed search engine, referred to as Físréal, which utilises inexpensive workstations, yet attains fast retrieval performance for Terabyte-sized collections. We also discuss the process of leveraging additional meaning from the structure of HTML, as well as the use of anchor text documents to increase retrieval performance.

We examine the effects of various query modifications on the problem of answer projection — the task of retrieving documents that support a given answer to a question. We compare different techniques such as phrase searches and term weighting, and show that some models achieve significant improvements over unmodified queries.

In this study, we present the analysis of the interconnection network of a distributed Information Retrieval (IR) system, by simulating a switched network versus a shared access network. The results show that the use of a switched network improves the performance, especially in a replicated system because the switched network prevents the saturation of the network, particularly when using a large number of query servers.