A Taxonomy of Information Retrieval Models and Tools

Information retrieval is attracting significant attention due to the exponential growth of the amount of information available in digital format. The proliferation of information retrieval objects, including algorithms, methods, technologies, and tools, makes it difficult to assess their capabilities and features and to understand the relationships that exist among them. In addition, the terminology is often confusing and misleading, as different terms are used to denote the same, or similar, tasks. This paper proposes a taxonomy of information retrieval models and tools and provides precise definitions for the key terms. The taxonomy consists of superimposing two views: a vertical taxonomy, that classifies IR models with respect to a set of basic features, and a horizontal taxonomy, which classifies IR systems and services with respect to the tasks they support. The aim is to provide a framework for classifying existing information retrieval models and tools and a solid point to assess future developments in the field

Long-term Information Preservation and Access

An unprecedented amount of information encompassing almost every facet of human activities across the world is generated daily in the form of zeros and ones, and that is often the only form in which such information is recorded. A good fraction of this information needs to be preserved for periods of time ranging from a few years to centuries. Consequently, the problem of preserving digital information over a long-term has attracted the attention of many organizations, including libraries, government agencies, scientific communities, and individual researchers. In this dissertation, we address three issues that are critical to ensure long-term information preservation and access. The first concerns the core requirement of how to guarantee the integrity of preserved contents. Digital information is in general very fragile because of the many ways errors can be introduced, such as errors introduced because of hardware and media degradation, hardware and software malfunction, operational errors, security breaches, and malicious alterations. To address this problem, we develop a new approach based on efficient and rigorous cryptographic techniques, which will guarantee the integrity of preserved contents with extremely high probability even in the presence of malicious attacks. Our prototype implementation of this approach has been deployed and actively used in the past years in several organizations, including the San Diego Super Computer Center, the Chronopolis Consortium, North Carolina State University, and more recently the Government Printing Office. Second, we consider another crucial component in any preservation system - searching and locating information. The ever-growing size of a long-term archive and the temporality of each preserved item introduce a new set of challenges to providing a fast retrieval of content based on a temporal query. The widely-used cataloguing scheme has serious scalability problems. The standard full-text search approach has serious limitations since it does not deal appropriately with the temporal dimension, and, in particular, is incapable of performing relevancy scoring according to the temporal context. To address these problems, we introduce two types of indexing schemes - a location indexing scheme, and a full-text search indexing scheme. Our location indexing scheme provides optimal operations for inserting and locating a specific version of a preserved item given an item ID and a time point, and our full-text search indexing scheme efficiently handles the scalability problem, supporting relevancy scoring within the temporal context at the same time. Finally, we address the problem of organizing inter-related data, so that future accesses and data exploration can be quickly performed. We, in particular, consider web contents, where we combine a link-analysis scheme with a graph partitioning scheme to put together more closely related contents in the same standard web archive container. We conduct experiments that simulate random browsing of preserved contents, and show that our data organization scheme greatly minimizes the number of containers needed to be accessed for a random browsing session. Our schemes have been tested against real-world data of significant scale, and validated through extensive empirical evaluations

Interim research assessment 2003-2005 - Computer Science

This report primarily serves as a source of information for the 2007 Interim Research Assessment Committee for Computer Science at the three technical universities in the Netherlands. The report also provides information for others interested in our research activities

Open-domain web-based multiple document : question answering for list questions with support for temporal restrictors

Tese de doutoramento, Informática (Ciências da Computação), Universidade de Lisboa, Faculdade de Ciências, 2015With the growth of the Internet, more people are searching for information on the Web. The combination of web growth and improvements in Information Technology has reignited the interest in Question Answering (QA) systems. QA is a type of information retrieval combined with natural language processing techniques that aims at finding answers to natural language questions. List questions have been widely studied in the QA field. These are questions that require a list of correct answers, making the task of correctly answering them more complex. In List questions, the answers may lie in the same document or spread over multiple documents. In the latter case, a QA system able to answer List questions has to deal with the fusion of partial answers. The current Question Answering state-of-the-art does not provide yet a good way to tackle this complex problem of collecting the exact answers from multiple documents. Our goal is to provide better QA solutions to users, who desire direct answers, using approaches that deal with the complex problem of extracting answers found spread over several documents. The present dissertation address the problem of answering Open-domain List questions by exploring redundancy and combining it with heuristics to improve QA accuracy. Our approach uses the Web as information source, since it is several orders of magnitude larger than other document collections. Besides handling List questions, we develop an approach with special focus on questions that include temporal information. In this regard, the current work addresses a topic that was lacking specific research. A additional purpose of this dissertation is to report on important results of the research combining Web-based QA, List QA and Temporal QA. Besides the evaluation of our approach itself we compare our system with other QA systems in order to assess its performance relative to the state-of-the-art. Finally, our approaches to answer List questions and List questions with temporal information are implemented into a fully-fledged Open-domain Web-based Question Answering System that provides answers retrieved from multiple documents.Com o crescimento da Internet cada vez mais pessoas buscam informações usando a Web. A combinação do crescimento da Internet com melhoramentos na Tecnologia da Informação traz como consequência o renovado interesse em Sistemas de Respostas a Perguntas (SRP). SRP combina técnicas de recuperação de informação com ferramentas de apoio à linguagem natural com o objetivo de encontrar respostas para perguntas em linguagem natural. Perguntas do tipo lista têm sido largamente estudadas nesta área. Neste tipo de perguntas é esperada uma lista de respostas corretas, o que torna a tarefa de responder a perguntas do tipo lista ainda mais complexa. As respostas para este tipo de pergunta podem ser encontradas num único documento ou espalhados em múltiplos documentos. No último caso, um SRP deve estar preparado para lidar com a fusão de respostas parciais. Os SRP atuais ainda não providenciam uma boa forma de lidar com este complexo problema de coletar respostas de múltiplos documentos. Nosso objetivo é prover melhores soluções para utilizadores que desejam buscar respostas diretas usando abordagens para extrair respostas de múltiplos documentos. Esta dissertação aborda o problema de responder a perguntas de domínio aberto explorando redundância combinada com heurísticas. Nossa abordagem usa a Internet como fonte de informação uma vez que a Web é a maior coleção de documentos da atualidade. Para além de responder a perguntas do tipo lista, nós desenvolvemos uma abordagem para responder a perguntas com restrição temporal. Neste sentido, o presente trabalho aborda este tema onde há pouca investigação específica. Adicionalmente, esta dissertação tem o propósito de informar sobre resultados importantes desta pesquisa que combina várias áreas: SRP com base na Web, SRP especialmente desenvolvidos para responder perguntas do tipo lista e também com restrição temporal. Além da avaliação da nossa própria abordagem, comparamos o nosso sistema com outros SRP, a fim de avaliar o seu desempenho em relação ao estado da arte. Por fim, as nossas abordagens para responder a perguntas do tipo lista e perguntas do tipo lista com informações temporais são implementadas em um Sistema online de Respostas a Perguntas de domínio aberto que funciona diretamente sob a Web e que fornece respostas extraídas de múltiplos documentos.Fundação para a Ciência e a Tecnologia (FCT), SFRH/BD/65647/2009; European Commission, projeto QTLeap (Quality Translation by Deep Language Engineering Approache

Evaluating Information Retrieval and Access Tasks

This open access book summarizes the first two decades of the NII Testbeds and Community for Information access Research (NTCIR). NTCIR is a series of evaluation forums run by a global team of researchers and hosted by the National Institute of Informatics (NII), Japan. The book is unique in that it discusses not just what was done at NTCIR, but also how it was done and the impact it has achieved. For example, in some chapters the reader sees the early seeds of what eventually grew to be the search engines that provide access to content on the World Wide Web, today’s smartphones that can tailor what they show to the needs of their owners, and the smart speakers that enrich our lives at home and on the move. We also get glimpses into how new search engines can be built for mathematical formulae, or for the digital record of a lived human life. Key to the success of the NTCIR endeavor was early recognition that information access research is an empirical discipline and that evaluation therefore lay at the core of the enterprise. Evaluation is thus at the heart of each chapter in this book. They show, for example, how the recognition that some documents are more important than others has shaped thinking about evaluation design. The thirty-three contributors to this volume speak for the many hundreds of researchers from dozens of countries around the world who together shaped NTCIR as organizers and participants. This book is suitable for researchers, practitioners, and students—anyone who wants to learn about past and present evaluation efforts in information retrieval, information access, and natural language processing, as well as those who want to participate in an evaluation task or even to design and organize one