Thesis (M.S.)--Rochester Institute of Technology, 1987. / Typescript. Includes bibliographical references (leaves 137-144).

Konstanz, Univ., Bachelorarb., 2004.

Este trabalho propõe a utilização de algoritmos de mineração de regras de associação para a Recuperação de Informações Multilíngues. Esses algoritmos têm sido amplamente utilizados para analisar transações de registro de vendas. A ideia é mapear o problema de encontrar associações entre itens vendidos para o problema de encontrar termos equivalentes entre idiomas diferentes em um corpus paralelo. A proposta foi validada por meio de experimentos com diferentes idiomas, conjuntos de consultas e corpora. Os resultados mostram que a eficácia da abordagem proposta é comparável ao estado da arte, ao resultado monolíngue e à tradução automática de consultas, embora este utilize técnicas mais complexas de processamento de linguagem natural. Foi criado um protótipo que faz consultas à Web utilizando o método proposto. O sistema recebe palavras-chave em português, as traduz para o inglês e submete a consulta a diversos sites de busca. / This work proposes the use of algorithms for mining association rules as an approach for Cross-Language Information Retrieval. These algorithms have been widely used to analyze market basket data. The idea is to map the problem of finding associations between sales items to the problem of finding term translations over a parallel corpus. The proposal was validated by means of experiments using different languages, queries and corpora. The results show that the performance of our proposed approach is comparable to the performance of the monolingual baseline and to query translation via machine translation, even though these systems employ more complex Natural Language Processing techniques. A prototype for cross-language web querying was implemented to test the proposed method. The system accepts keywords in Portuguese, translates them into English and submits the query to several web-sites that provide search functionalities.

Este trabalho propõe a utilização de algoritmos de mineração de regras de associação para a Recuperação de Informações Multilíngues. Esses algoritmos têm sido amplamente utilizados para analisar transações de registro de vendas. A ideia é mapear o problema de encontrar associações entre itens vendidos para o problema de encontrar termos equivalentes entre idiomas diferentes em um corpus paralelo. A proposta foi validada por meio de experimentos com diferentes idiomas, conjuntos de consultas e corpora. Os resultados mostram que a eficácia da abordagem proposta é comparável ao estado da arte, ao resultado monolíngue e à tradução automática de consultas, embora este utilize técnicas mais complexas de processamento de linguagem natural. Foi criado um protótipo que faz consultas à Web utilizando o método proposto. O sistema recebe palavras-chave em português, as traduz para o inglês e submete a consulta a diversos sites de busca. / This work proposes the use of algorithms for mining association rules as an approach for Cross-Language Information Retrieval. These algorithms have been widely used to analyze market basket data. The idea is to map the problem of finding associations between sales items to the problem of finding term translations over a parallel corpus. The proposal was validated by means of experiments using different languages, queries and corpora. The results show that the performance of our proposed approach is comparable to the performance of the monolingual baseline and to query translation via machine translation, even though these systems employ more complex Natural Language Processing techniques. A prototype for cross-language web querying was implemented to test the proposed method. The system accepts keywords in Portuguese, translates them into English and submits the query to several web-sites that provide search functionalities.

Este trabalho propõe a utilização de algoritmos de mineração de regras de associação para a Recuperação de Informações Multilíngues. Esses algoritmos têm sido amplamente utilizados para analisar transações de registro de vendas. A ideia é mapear o problema de encontrar associações entre itens vendidos para o problema de encontrar termos equivalentes entre idiomas diferentes em um corpus paralelo. A proposta foi validada por meio de experimentos com diferentes idiomas, conjuntos de consultas e corpora. Os resultados mostram que a eficácia da abordagem proposta é comparável ao estado da arte, ao resultado monolíngue e à tradução automática de consultas, embora este utilize técnicas mais complexas de processamento de linguagem natural. Foi criado um protótipo que faz consultas à Web utilizando o método proposto. O sistema recebe palavras-chave em português, as traduz para o inglês e submete a consulta a diversos sites de busca. / This work proposes the use of algorithms for mining association rules as an approach for Cross-Language Information Retrieval. These algorithms have been widely used to analyze market basket data. The idea is to map the problem of finding associations between sales items to the problem of finding term translations over a parallel corpus. The proposal was validated by means of experiments using different languages, queries and corpora. The results show that the performance of our proposed approach is comparable to the performance of the monolingual baseline and to query translation via machine translation, even though these systems employ more complex Natural Language Processing techniques. A prototype for cross-language web querying was implemented to test the proposed method. The system accepts keywords in Portuguese, translates them into English and submits the query to several web-sites that provide search functionalities.

Orientador: Claudia Maria Bauzer Medeiros / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação / Made available in DSpace on 2018-08-15T17:25:33Z (GMT). No. of bitstreams: 1 Sousa_SidneyRobertode_M.pdf: 6639415 bytes, checksum: fbd426bff26dda1788b1310f9167190c (MD5) Previous issue date: 2010 / Resumo: Sistemas de informação geográfica a cada vez mais utilizam informação geo-espacial da Web para produzir informação geográfica. Um grande desafio para tais sistemas é encontrar dados relevantes, onde tal busca é frequentemente baseada em palavras-chave ou nome de arquivos. Porém, tais abordagens carecem de semântica. Desta forma, torna-se necessário oferecer mecanismos para preparação de dados, afim de auxiliar a recuperação de dados semanticamente relevantes. Para atacar este problema, esta dissertação de mestrado propôem uma arquitetura baseada em serviços para gerenciar anotações semânticas. Neste trabalho, uma anotação semântica é um conjunto de triplas - chamadas unidades de anotação semântica - <subject, metadata field, object >, onde subject é um documento geo-espacial, (metadata field) é um campo de metadados sobre este documento e object é um termo de ontologia que associa semanticamente o campo de metadados a algum conceito apropriado. As principais contribuições desta dissertação são: um estudo comparativo sobre ferramentas de anotação; especificação e implementação de uma arquitetura baseada em serviços para gerenciar anotações semânticas, incluindo serviços para manuseio de termos de ontologias; e uma análise comparativa de mecanismos para armazenar anotações semânticas. O trabalho toma como estudo de caso anotações semânticas sobre documentos agrícolas / Abstract: Geographic information systems (GIS) are increasingly using geospatial data from the Web to produce geographic information. One big challenge is to find the relevant data, which often is based on keywords or even file names. However, these approaches lack semantics. Thus, it is necessary to provide mechanisms to prepare data to help retrieval of semantically relevant data. To attack this problem, this dissertation proposes a service-based architecture to manage semantic annotations. In this work, a semantic annotation is a set of triples - called semantic annotation units - < subject? metadata field? object >, where subject is a geospatial resource, (metadata field) contains some characteristic about this resource, and object is an ontology term that semantically associates the metadata field to some appropriate concept. The main contributions of this dissertation are: a comparative study on annotation tools; specification and implementation of a service-based architecture to manage semantic annotations, including services for handling ontology terms; and a comparative analysis of mechanisms for storing semantic annotations. The work takes as case study semantic annotations about agricultural resources / Mestrado / Banco de Dados / Mestre em Ciência da Computação

In this thesis, we propose a new approach to Chinese-English Biomedical cross-lingual information retrieval (CLIR) using query expansion based on the eCMeSH Tree, a Chinese-English ontology extended from the Chinese Medical Subject Headings (CMeSH) Tree. The CMeSH Tree is not designed for information retrieval (IR), since it only includes heading terms and has no term weighting scheme for these terms. Therefore, we design an algorithm, which employs a rule-based parsing technique combined with the C-value term extraction algorithm and a filtering technique based on mutual information, to extract Chinese synonyms for the corresponding heading terms. We also develop a term-weighting mechanism. Following the hierarchical structure of CMeSH, we extend the CMeSH Tree to the eCMeSH Tree with synonymous terms and their weights. We propose an algorithm to implement CLIR using the eCMeSH Tree terms to expand queries. In order to evaluate the retrieval improvements obtained from our approach, the results of the query expansion based on the eCMeSH Tree are individually compared with the results of the experiments of query expansion using the CMeSH Tree terms, query expansion using pseudo-relevance feedback, and document translation. We also evaluate the combinations of these three approaches. This study also investigates the factors which affect the CLIR performance, including a stemming algorithm, retrieval models, and word segmentation.

Our generation has experienced one of the most dramatic changes in how society communicates. Today, we have online information on almost any imaginable topic. However, most of this information is available in only a few dozen languages. In this thesis, I explore the use of parallel texts to enable cross-language information retrieval (CLIR) for languages with scarce resources. To build the parallel text I use the Bible. I evaluate different variables and their impact on the resulting CLIR system, specifically: (1) the CLIR results when using different amounts of parallel text; (2) the role of paraphrasing on the quality of the CLIR output; (3) the impact on accuracy when translating the query versus translating the collection of documents; and finally (4) how the results are affected by the use of different dialects. The results show that all these variables have a direct impact on the quality of the CLIR system.

In recent years, geography has acquired a great importance in the context of Information Retrieval (IR) and, in general, of the automated processing of information in text. Mobile devices that are able to surf the web and at the same time inform about their position are now a common reality, together with applications that can exploit this data to provide users with locally customised information, such as directions or advertisements. Therefore, it is important to deal properly with the geographic information that is included in electronic texts. The majority of such kind of information is contained as place names, or toponyms. Toponym ambiguity represents an important issue in Geographical Information Retrieval (GIR), due to the fact that queries are geographically constrained. There has been a struggle to nd speci c geographical IR methods that actually outperform traditional IR techniques. Toponym ambiguity may constitute a relevant factor in the inability of current GIR systems to take advantage from geographical knowledge. Recently, some Ph.D. theses have dealt with Toponym Disambiguation (TD) from di erent perspectives, from the development of resources for the evaluation of Toponym Disambiguation (Leidner (2007)) to the use of TD to improve geographical scope resolution (Andogah (2010)). The Ph.D. thesis presented here introduces a TD method based on WordNet and carries out a detailed study of the relationship of Toponym Disambiguation to some IR applications, such as GIR, Question Answering (QA) and Web retrieval. The work presented in this thesis starts with an introduction to the applications in which TD may result useful, together with an analysis of the ambiguity of toponyms in news collections. It could not be possible to study the ambiguity of toponyms without studying the resources that are used as placename repositories; these resources are the equivalent to language dictionaries, which provide the di erent meanings of a given word. / Buscaldi, D. (2010). Toponym Disambiguation in Information Retrieval [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/8912 / Palancia

This thesis is focused on information retrieval in the context of its historical development, it presents trends in integration of intelligent features in it, and thus the emergence of intelligent information retrieval. Individual intelligent elements are described in a separate chapter, following chapter then introduces their use, including specific examples. Thesis also traces research on the topic of intelligent information retrieval in selected institutions both in the Czech republic and abroad; results of this survey for Czech republic are presented in the enclosed search.