Distributed Information Retrieval (DIR) is a generic area of research that brings together techniques, such as resource selection and results aggregation, dealing with data that, for organizational or technical reasons, cannot be managed centrally. Existing and potential applications of DIR methods vary from blog retrieval to aggregated search and from multimedia and multilingual retrieval to d...

This paper presents a novel concept for resource management in cluster-based image retrieval systems. First, the paper describes image retrieval using static and dynamic feature extraction. The complexity of dynamic feature extraction requires the utilization of powerful parallel architectures and in order to provide the user with reasonable response times. Most existing methods for resource ma...

Resource selection is an important topic in distributed information retrieval research. It can be a component of a distributed information retrieval task and can also serve as an independent application of database recommendation system together with the resource representation part. There is a large body of valuable prior research on resource selection but very little has studied about the eff...

In a federated digital library system, it is too expensive to query every accessible library. Resource selection is the task to decide to which libraries a query should be passed. Most existing resource selection algorithms compute a library ranking in a heuristic way. In this paper, we follow a different approach on a better theoretic foundation. The decision-theoretic approach tries to minimi...

The paper introduces the architecture and functionality of the knowledge-based information retrieval technology developed at Vertical Search Works. A large-scale language-independent ontology is used during indexing, query analysis, and document retrieval as part of a web-scale vertical search engine. Three specific areas are examined: the knowledge resource, its visualization and editing toolb...

When searching information in a retrieval system people use a variety of terms to describe their information needs When the terms used in a query are di erent from those indexed by the system users fail to obtain the information they want This is called the vocabulary problem This problem has been studied and discussed in information retrieval for decades Recently Deerwester et al proposed a ne...

purpose: the aim of this paper is to survey the rate of the precision in the audio and visual material retrieval by clustering techniques and k- means algorithm. methodology: the type of the research method is experimental. for the purpose of this paper, twenty- three albums are studied directly through observation. albums published in summer 1391(solar). songs catalogs according to pbcore meta...

The distributed retrieval process is plagued by uncertainty. Sampling, selection, merging and ranking are all based on very limited information compared to centralized retrieval. In this paper, we focus our attention on reducing the uncertainty within the resource selection phase by obtaining a number of estimates, rather than relying upon only one point estimate. We propose three methods for r...

This paper presents a domain-oriented user attribute model for getting user personalized and real requirements on the field of the accurate retrieval. Resource Distribution Matrix (RDM) and User’s Personalized Preference Vector (UPPV) are created by analyzing the user feature and resource characteristic on domain – specific condition. We then present a method to improve the efficiency of the pe...