TESQUAL: A Microthesaurus for Use in Quality Management in European Higher Education

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Application of Information Retrieval Techniques to Heterogeneous Databases in the Virtual Distributed Laboratory

The Department of Defense (DoD) maintains thousands of Synthetic Aperture Radar (SAR), Infrared (IR), Hyper-Spectral intelligence imagery and Electro-Optical (EO) target signature data. These images are essential to evaluating and testing individual algorithm methodologies and development techniques within the Automatic Target Recognition (ATR) community. The Air Force Research Laboratory Sensors Directorate (AFRL/SN) has proposed the Virtual Distributed Laboratory (VDL) to maintain a central collection of the associated imagery metadata and a query mechanism to retrieve the desired imagery. All imagery metadata is stored in relational database format for access from agencies throughout the federal government and large civilian universities. Each set of imagery is independently maintained at each agency s location along with a local copy of the associated metadata that is periodically updated and sent to the VDL. This research focuses on applying information retrieval techniques to the multiple heterogeneous imagery metadata databases to present users the most relevant images based on user defined search criteria. More specifically, it defines a hierarchical concept thesaurus development methodology to handle the complexities of heterogeneous databases and the application of two classic information retrieval models. The results indicate this type of thesaurus-based approach can significantly increase the precision and recall levels of retrieving relevant documents

Improving search engines with open Web-based SKOS vocabularies

Dissertação para obtenção do Grau de Mestre em Engenharia InformáticaThe volume of digital information is increasingly larger and even though organiza-tions are making more of this information available, without the proper tools users have great difficulties in retrieving documents about subjects of interest. Good infor-mation retrieval mechanisms are crucial for answering user information needs. Nowadays, search engines are unavoidable - they are an essential feature in docu-ment management systems. However, achieving good relevancy is a difficult problem particularly when dealing with specific technical domains where vocabulary mismatch problems can be prejudicial. Numerous research works found that exploiting the lexi-cal or semantic relations of terms in a collection attenuates this problem. In this dissertation, we aim to improve search results and user experience by inves-tigating the use of potentially connected Web vocabularies in information retrieval en-gines. In the context of open Web-based SKOS vocabularies we propose a query expan-sion framework implemented in a widely used IR system (Lucene/Solr), and evaluated using standard IR evaluation datasets. The components described in this thesis were applied in the development of a new search system that was integrated with a rapid applications development tool in the context of an internship at Quidgest S.A.Fundação para a Ciência e Tecnologia - ImTV research project, in the context of the UTAustin-Portugal collaboration (UTA-Est/MAI/0010/2009); QSearch project (FCT/Quidgest

CLEF 2005: Ad Hoc track overview

We describe the objectives and organization of the CLEF 2005 ad hoc track and discuss the main characteristics of the tasks offered to test monolingual, bilingual and multilingual textual document retrieval. The performance achieved for each task is presented and a preliminary analysis of results is given. The paper focuses in particular on the multilingual tasks which reused the test collection created in CLEF 2003 in an attempt to see if an improvement in system performance over time could be measured, and also to examine the multilingual results merging problem

Western States Dublin Core Metadata Best Practices, version 1.2

Funded by a grant awarded by the Institute for Museum and Library Services (IMLS) in the fall of 2001, the University of Denver (Denver, Colorado) spearheaded a multi-state collaborative initiative to create a virtual collection of widely dispersed digital resources on the topic, Western trails. As part of this initiative, 23 institutions in four Western states were awarded mini-grants to create digital content and metadata for resources related to Western trails. In addition to creation of a virtual collection of digital resources, another significant component of this multi-state initiative was development of a set of Dublin-Core based best practices by representatives from cultural heritage institutions beyond the original four participating states. Accordingly, in March 2002, 18 representatives from eight Western states met in Denver, Colorado to begin exploring issues associated with application of Dublin Core to digital objects by cultural heritage institutions. This group, the Western States Digital Standards Group (WSDSG) Metadata Working Group, formed two task forces to develop guidelines for the Dublin Core metadata. The WSDSG Metadata Working Group met again in Topeka, Kansas in July 2002 to finalize the guidelines and determine the remaining components of a best practices document. In November 2002 the resultant WSDSG Guidelines for the Dublin Core Elements were posted on the Colorado Digitization Program (CDP) and the Western Trails project website. In January 2003, the WSDSG Best Practices document will be released. This Best Practices document is based upon and supercedes the CDP’s General Guidelines for Descriptive Metadata Creation and Metadata

CRIS-IR 2006

The recognition of entities and their relationships in document collections is an important step towards the discovery of latent knowledge as well as to support knowledge management applications. The challenge lies on how to extract and correlate entities, aiming to answer key knowledge management questions, such as; who works with whom, on which projects, with which customers and on what research areas. The present work proposes a knowledge mining approach supported by information retrieval and text mining tasks in which its core is based on the correlation of textual elements through the LRD (Latent Relation Discovery) method. Our experiments show that LRD outperform better than other correlation methods. Also, we present an application in order to demonstrate the approach over knowledge management scenarios.Fundação para a Ciência e a Tecnologia (FCT) Denmark's Electronic Research Librar