In this paper we present a systematic analysis of document retrieval using unstructured and structured queries within the score region algebra (SRA) structured retrieval framework. The behavior of different retrieval models, namely Boolean, tf.idf, GPX, language models, and Okapi, is tested using the transparent SRA framework in our three-level structured retrieval system called TIJAH. The retr...

This paper describes an application of support vector machines (SVMs) to interactive document retrieval using active learning. We show that an SVM-based retrieval has an association with conventional Rocchio-based relevance feedback by a comparative analysis. We propose a cosine kernel, which denotes cosine similarity, suitable for an SVM-based interactive document retrieval based on the analys...

Relevant contributions of fuzzy logic to the logical models in information retrieval is studied. It makes it possible to grasp the graduality of some relevant concepts and to model both imprecision and uncertainty inherent to the retrieval process, still in the framework of the broadly meant logical approach. In this perspective we discuss various extensions to the basic Boolean model which are...

The paper proposes a preprocessing scheme for efficient processing of XML queries in XML-based information retrieval systems. For the preprocessing, we use a signature-based approach. In the conventional (flat document-based) information retrieval systems, user queries consist of keywords and boolean operators, and thus signatures are structured in a flat manner. However, in XML-based informati...

The performance of an information retrieval system is usually measured in terms of two different criteria, precision and recall. This way, the optimization of any of its components is a clear example of a multiobjective problem. However, although evolutionary programming have been widely applied in the information retrieval area, in all of these applications both criteria have been combined in ...

SUMMARY In many practical information retrieval situations, it is necessary to process heterogeneous text databases that vary greatly in scope and coverage, and deal with many different subjects. In such an environment it is important to provide flexible access to individual text pieces, and to structure the collection so that related text elements are identified and appropriately linked. Metho...

This article presents a genetic learning algorithm to derive discrete patterns that can be used for classification and retrieval of 3D motion capture data. Based on boolean motion features, the idea is to learn motion class patterns in an evolutionary process with the objective to discriminate a given set of positive from a given set of negative training motions. Here, the fitness of a pattern ...

The Berkeley experiments for TREC-5 extend those of TREC-4 in numerous ways. For routing retrieval we experimented with the idea of term importance in three ways -training on Boolean conjuncts of the most important terms, filtering with the most important terms, and, finally, logistic regression on presence or absence of those terms. For ad-hoc retrieval we retained the manual reformulations of...

The PIRCS retrieval system has been upgraded in TREC-3 to handle the full English collections of 2 GB in an efficient manner. For ad-hoc retrieval, we use recurrent spreading of activation in our network to implement query learning and expansion based on the best-ranked subdocuments of an initial retrieval. We also augment our standard retrieval algorithm with a soft-Boolean component. For rout...

Many advanced models have been developed for information retrieval over the last years. These models are built on various artificial intelligence paradigms to improve the precision of the retrieval. Most of them exploit some form of term co-occurrences to improve retrieval quality. In this paper, we compare the retrieval performance of five of these models: the Extended Boolean model, the Gener...