Desde o seu nascimento, a Ciência da Informação vem estudando métodos para o tratamento automático da informação. Esta pesquisa centrou-se na Recuperação de Informação, área que envolve a aplicação de métodos computacionais no tratamento e recuperação da informação, para avaliar em que medida a Ciência da Computação contribui para o avanço da Ciência da Informação. Inicialmente a Recuperação de Informação é contextualizada no corpo interdisciplinar da Ciência da Informação e são apresentados os elementos básicos do processo de recuperação de informação. Os modelos computacionais de recuperação de informação são analisados a partir da categorização em “quantitativos” e “dinâmicos”. Algumas técnicas de processamento da linguagem natural utilizadas na recuperação de informação são igualmente discutidas. No contexto atual da Web são apresentadas as técnicas de representação e recuperação da informação desde os mecanismos de busca até a Web Semântica. Conclui-se que, apesar da inquestionável importância dos métodos e técnicas computacionais no tratamento da informação, estas se configuram apenas como ferramentas auxiliares, pois utilizam uma conceituação de “informação” extremamente restrita em relação àquela utilizada pela Ciência da Informação; Since its birth...

A mineração de grandes coleções de textos, imagens e outros tipos de documentos tem se mostrado uma forma efetiva para exploração e interação com grandes quantidades de informações disponíveis, principalmente na World Wide Web. Neste contexto, diversos trabalhos têm tratado de mineração tanto de coleções estáticas quanto de coleções dinâmicas de objetos. Adicionalmente, técnicas de visualização têm sido propostas para auxiliar o processo de entendimento e de exploração dessas coleções, permitindo que a interação do usuário melhore o processo de mineração (user in the loop). No caso específico de dados dinâmicos, foi desenvolvido por Roberto Pinho e colegas uma técnica incremental (IncBoard) com o objetivo de visualizar coleções dinâmicas de elementos. Tal técnica posiciona os elementos em um grid bidimensional baseado na similaridade de conteúdo entre os elementos. Procura-se manter elementos similares próximos no grid. A técnica foi avaliada em um processo que simulava a chegada de novos dados, apresentando iterativamente novos elementos a serem posicionados no mapa corrente. Observa-se, entretanto, que um aspecto importante de tal ferramenta seria a possibilidade de novos elementos - a serem exibidos no mapa...

Com a crescente popularidade da World Wide Web mais pessoas têm acesso à informação cujo volume vem expandindo ao longo do tempo. A área de recuperação de informação ganhou um novo desafio visando buscar os recursos pelo significado da informação neles contida. Uma forma de recuperar a informação, pelo seu significado, é pelo uso de uma base de conhecimento que modela os conceitos de um domínio e seus relacionamentos. Atualmente, ontologias têm sido utilizadas para modelar bases de conhecimento. Para tratar com a imprecisão e a incerteza, presentes no conhecimento e no processo de recuperação de informação, são empregadas técnicas da teoria de conjuntos fuzzy. Trabalhos precedentes codificam a base de conhecimento utilizando apenas uma ontologia. Entretanto, uma coleção de documentos pode tratar temas pertencentes a domínios diferentes, expressos por ontologias distintas, que podem estar relacionados. Neste trabalho, uma forma de organização e representação do conhecimento em múltiplas ontologias relacionadas foi investigada e um novo método de expansão de consulta foi desenvolvido. A organização do conhecimento e o método de expansão de consulta foram integrados no modelo fuzzy para recuperação de informação utilizando múltiplas ontologias relacionadas. O desempenho do modelo foi comparado com outro modelo fuzzy para recuperação de informação e com a máquina de busca Lucene do projeto Apache. Em ambos os casos o modelo proposto apresentou uma melhora nas medidas de precisão e cobertura; With the World Wide Web popularity growth...

Published methods for distributed information retrieval generally rely on cooperation from search servers. But most real servers, particularly the tens of thousands available on the Web, are not engineered for such cooperation. This means that the majority of methods proposed, and evaluated in simulated environments of homogeneous cooperating servers, are never applied in practice. ¶ This thesis introduces new methods for server selection and results merging. The methods do not require search servers to cooperate, yet are as effective as the best methods which do. Two large experiments evaluate the new methods against many previously published methods. In contrast to previous experiments they simulate a Web-like environment, where servers employ varied retrieval algorithms and tend not to sub-partition documents from a single source. ...; yes

La evaluación de los Sistemas de recuperación de información se ha des-arrollado paralelamente a su evolución por razones de carácter científico. Así, han aparecido un gran número de propuestas para llevar a cabo este proceso. En cual-quier caso y dando por sentado que cada una de las propuestas realizadas -la mayo-ría de las cuales se presentan en este trabajo- tratan de buscar un mecanismo robusto para medir el comportamiento de la recuperación de información, no es menos cierto que nos enfrentamos a un problema complejo y que en definitiva tienen como obje-tivo encontrar un método que permitiese seleccionar el mejor modo de recuperación dada una necesidad de información de un usuario. Este el es el eje donde gravita el escenario de la evaluación de la recuperación de información.; ABSTRACT: The evaluation of Information Retrieval Systems has been developed parallelly to their evolution for reasons of scientific nature, generating the appearance of a great number of proposals to make this process. Assuming that all these propos-als - most of which they appear in this worktry to look for a robust mechanism to measure the effectiveness of Information Retrieval Systems, it is not less certain information retrieval is a complex problem to resolve...

Le domaine biomédical est probablement le domaine où il y a les ressources les plus riches. Dans ces ressources, on regroupe les différentes expressions exprimant un concept, et définit des relations entre les concepts. Ces ressources sont construites pour faciliter l’accès aux informations dans le domaine. On pense généralement que ces ressources sont utiles pour la recherche d’information biomédicale. Or, les résultats obtenus jusqu’à présent sont mitigés : dans certaines études, l’utilisation des concepts a pu augmenter la performance de recherche, mais dans d’autres études, on a plutôt observé des baisses de performance. Cependant, ces résultats restent difficilement comparables étant donné qu’ils ont été obtenus sur des collections différentes. Il reste encore une question ouverte si et comment ces ressources peuvent aider à améliorer la recherche d’information biomédicale. Dans ce mémoire, nous comparons les différentes approches basées sur des concepts dans un même cadre, notamment l’approche utilisant les identificateurs de concept comme unité de représentation, et l’approche utilisant des expressions synonymes pour étendre la requête initiale. En comparaison avec l’approche traditionnelle de "sac de mots"...

This paper investigates the impact of three approaches to XML retrieval: using Zettair, a full-text information retrieval system; using eXist, a native XML database; and using a hybrid system that takes full article answers from Zettair and uses eXist to extract elements from those articles. For the content-only topics, we undertake a preliminary analysis of the INEX 2003 relevance assessments in order to identify the types of highly relevant document components. Further analysis identifies two complementary sub-cases of relevance assessments ("General" and "Specific") and two categories of topics ("Broad" and "Narrow"). We develop a novel retrieval module that for a content-only topic utilises the information from the resulting answer list of a native XML database and dynamically determines the preferable units of retrieval, which we call "Coherent Retrieval Elements". The results of our experiments show that -- when each of the three systems is evaluated against different retrieval scenarios (such as different cases of relevance assessments, different topic categories and different choices of evaluation metrics) -- the XML retrieval systems exhibit varying behaviour and the best performance can be reached for different values of the retrieval parameters. In the case of INEX 2003 relevance assessments for the content-only topics...

Three approaches to content-and-structure XML retrieval are analysed in this paper: first by using Zettair, a full-text information retrieval system; second by using eXist, a native XML database, and third by using a hybrid XML retrieval system that uses eXist to produce the final answers from likely relevant articles retrieved by Zettair. INEX 2003 content-and-structure topics can be classified in two categories: the first retrieving full articles as final answers, and the second retrieving more specific elements within articles as final answers. We show that for both topic categories our initial hybrid system improves the retrieval effectiveness of a native XML database. For ranking the final answer elements, we propose and evaluate a novel retrieval model that utilises the structural relationships between the answer elements of a native XML database and retrieves Coherent Retrieval Elements. The final results of our experiments show that when the XML retrieval task focusses on highly relevant elements our hybrid XML retrieval system with the Coherent Retrieval Elements module is 1.8 times more effective than Zettair and 3 times more effective than eXist, and yields an effective content-and-structure XML retrieval.

The modern geographic information retrieval technology is based on quantitative models and methods. The semantic information in web documents and queries cannot be effectively represented, leading to information lost or misunderstanding so that the results are either unreliable or inconsistent. A new qualitative approach is thus proposed for supporting geographic information retrieval based on qualitative representation, semantic matching, and qualitative reasoning. A qualitative representation model and the corresponding similarity measurement method are defined. Information in documents and user queries are represented using propositional logic, which considers the thematic and geographic semantics synthetically. Thematic information is represented as thematic propositions on the base of domain ontology. Similarly, spatial information is represented as geo-spatial propositions with the support of geographic knowledge base. Then the similarity is divided into thematic similarity and spatial similarity. The former is calculated by the weighted distance of proposition keywords in the domain ontology, and the latter similarity is further divided into conceptual similarity and spatial similarity. Represented by propositions and information units...

In computer interfaces in general, especially in information retrieval tasks, it is important to be able to quickly find and retrieve information. State of the art approach, used, for example, in search engines, is not effective as it introduces losses of meanings due to context to keywords back and forth translation. Authors argue it increases the time and reduces the accuracy of information retrieval compared to what it could be in the system that employs modern information retrieval and text mining methods while presenting results in an adaptive human- computer interface where system effectively learns what operator needs through iterative interaction. In current work, a combination of adaptive navigational interface and real time collaborative feedback analysis for documents relevance weighting is proposed as an viable alternative to prevailing "telegraphic" approach in information retrieval systems. Adaptive navigation is provided through a dynamic links panel controlled by an evolutionary algorithm. Documents relevance is initially established with standard information retrieval techniques and is further refined in real time through interaction of users with the system. Introduced concepts of multidimensional Knowledge Map and Weighted Point of Interest allow finding relevant documents and users with common interests through a trivial calculation. Browsing search approach...

We consider information retrieval when the data, for instance multimedia, is coputationally expensive to fetch. Our approach uses "information filters" to considerably narrow the universe of possiblities before retrieval. We are especially interested in redundant information filters that save time over more general but more costly filters. Efficient retrieval requires that decision must be made about the necessity, order, and concurrent processing of proposed filters (an "execution plan"). We develop simple polynomial-time local criteria for optimal execution plans, and show that most forms of concurrency are suboptimal with information filters. Although the general problem of finding an optimal execution plan is likely exponential in the number of filters, we show experimentally that our local optimality criteria, used in a polynomial-time algorithm, nearly always find the global optimum with 15 filters or less, a sufficient number of filters for most applications. Our methods do not require special hardware and avoid the high processor idleness that is characteristic of massive parallelism solutions to this problem. We apply our ideas to an important application, information retrieval of cpationed data using natural-language understanding...

This decade has seen a great deal of progress in the development of information retrieval systems. Unfortunately, we still lack a systematic understanding of the behavior of the systems and their relationship with documents. In this paper we present a completely new approach towards the understanding of the information retrieval systems. Recently, it has been observed that retrieval systems in TREC 6 show some remarkable patterns in retrieving relevant documents. Based on the TREC 6 observations, we introduce a geometric linear model of information retrieval systems. We then apply the model to predict the number of relevant documents by the retrieval systems. The model is also scalable to a much larger data set. Although the model is developed based on the TREC 6 routing test data, I believe it can be readily applicable to other information retrieval systems. In Appendix, we explained a simple and efficient way of making a better system from the existing systems.; Comment: 13 pages

This first "Bibliometric-enhanced Information Retrieval" (BIR 2014) workshop aims to engage with the IR community about possible links to bibliometrics and scholarly communication. Bibliometric techniques are not yet widely used to enhance retrieval processes in digital libraries, although they offer value-added effects for users. In this workshop we will explore how statistical modelling of scholarship, such as Bradfordizing or network analysis of co-authorship network, can improve retrieval services for specific communities, as well as for large, cross-domain collections. This workshop aims to raise awareness of the missing link between information retrieval (IR) and bibliometrics / scientometrics and to create a common ground for the incorporation of bibliometric-enhanced services into retrieval at the digital library interface. Our interests include information retrieval, information seeking, science modelling, network analysis, and digital libraries. The goal is to apply insights from bibliometrics, scientometrics, and informetrics to concrete practical problems of information retrieval and browsing.; Comment: 4 pages, Bibliometric-enhanced Information Retrieval Workshop at ECIR 2014, Amsterdam, NL

Recent advances in the development of the low-cost, power-efficient embedded devices, coupled with the rising need for support of new information processing paradigms such as smart spaces and military surveillance systems, have led to active research in large-scale, highly distributed sensor networks of small, wireless, low-power, unattended sensors and actuators. While applications keep diversifying, one common property they share is the need for an efficient network architecture tailored towards information retrieval in sensor networks. Previous solutions designed for traditional networks serve as good references; however, due to the vast differences between previous paradigms and needs of sensor networks, a framework is required to gather and impart only the required information .To achieve this goal in this paper we have proposed a framework for intelligent information retrieval and dissemination to desired destination node. The proposed frame work combines three major concern areas in WSNs i.e. data aggregation, information retrieval and data dissemination in a single scenario. In the proposed framework data aggregation is responsible for combining information from all nodes and removing the redundant data. Information retrieval filters the processed data to obtain final information termed as intelligent data to be disseminated to the required destination node.; Comment: 5 pages...

This workshop brings together experts of communities which often have been perceived as different once: bibliometrics / scientometrics / informetrics on the one side and information retrieval on the other. Our motivation as organizers of the workshop started from the observation that main discourses in both fields are different, that communities are only partly overlapping and from the belief that a knowledge transfer would be profitable for both sides. Bibliometric techniques are not yet widely used to enhance retrieval processes in digital libraries, although they offer value-added effects for users. On the other side, more and more information professionals, working in libraries and archives are confronted with applying bibliometric techniques in their services. This way knowledge exchange becomes more urgent. The first workshop set the research agenda, by introducing in each other methods, reporting about current research problems and brainstorming about common interests. This follow-up workshop continues the overall communication, but also puts one problem into the focus. In particular, we will explore how statistical modelling of scholarship can improve retrieval services for specific communities, as well as for large, cross-domain collections like Mendeley or ResearchGate. This second BIR workshop continues to raise awareness of the missing link between Information Retrieval (IR) and bibliometrics and contributes to create a common ground for the incorporation of bibliometric-enhanced services into retrieval at the scholarly search engine interface.; Comment: 4 pages...

The combination of informetric analysis and information retrieval allows a twofold application. (1) While in-formetrics analysis is primarily used to gain insights into a scientific domain, it can be used to build recommen-dation or alternative ranking services. They are usually based on methods like co-occurrence or citation analyses. (2) Information retrieval and its decades-long tradition of rigorous evaluation using standard document corpora, predefined topics and relevance judgements can be used as a test bed for informetric analyses. We show a preliminary experiment on how both domains can be connected using the iSearch test collection, a standard information retrieval test collection derived from the open access arXiv.org preprint server. In this paper the aim is to draw a conclusion about the appropriateness of iSearch as a test bed for the evaluation of a retrieval or recommendation system that applies informetric methods to improve retrieval results for the user. Based on an interview study with physicists, bibliographic coupling and author-co-citation analysis, important authors for ten different research questions are identified. The results show that the analysed corpus includes these authors and their corresponding documents. This study is a first step towards a combination of retrieval evaluations and the evaluation of informetric analyses methods.; Comment: 6 pages...

The continuous increasing in the amount of the published and stored information requires a special Information Retrieval (IR) frameworks to search and get information accurately and speedily. Currently, keywords-based techniques are commonly used in information retrieval. However, a major drawback of the keywords approach is its inability of handling the polysemy and synonymy phenomenon of the natural language. For instance, the meanings of words and understanding of concepts differ in different communities. Same word use for different concepts (polysemy) or use different words for the same concept (synonymy). Most of information retrieval frameworks have a weakness to deal with the semantics of the words in term of (indexing, Boolean model, Latent Semantic Analysis (LSA) , Latent semantic Index (LSI) and semantic ranking, etc.). Traditional Arabic Information Retrieval (AIR) models performance insufficient with semantic queries, which deal with not only the keywords but also with the context of these keywords. Therefore, there is a need for a semantic information retrieval model with a semantic index structure and ranking algorithm based on semantic index.

Suppose there is a movie you would be interested in watching via pay-per-view, but you refuse to purchase the feed because you believe that the supplier will sell your information to groups paying for the contact information of all the people who purchased that movie, and the association of your name to that purchase could hinder career, relationships, or increase the amount of time you spend cleaning SPAM out of your mailbox. Private Information Retrieval (PIR) will allow you to retrieve a particular feed without the supplier knowing which feed you actually got, and Symmetric Private Information Retrieval (SPIR) will assure the supplier, if the feeds are equally priced, that you received only the number of feeds you purchased. Now you can purchase without risking your name being associated with a particular feed and the supplier has gained the business of a once paranoid client. The problem of SPIR can be achieved with the cryptographic primitive Oblivious Transfer (OT). Several approaches to constructing such protocols have been posed and proven to be secure. Most attempts have aimed at reducing the amount of communication, theoretically, but this thesis compares the computational expense of the algorithms through experimentation to show that reduction of communication is less valuable in the effort of achieving a practical protocol than reducing the amount of computation. Further...

Suppose there is a movie you would be interested in watching via pay-per-view, but you refuse to purchase the feed because you believe that the supplier will sell your information to groups paying for the contact information of all the people who purchased that movie, and the association of your name to that purchase could hinder career, relationships, or increase the amount of time you spend cleaning SPAM out of your mailbox. Private Information Retrieval (PIR) will allow you to retrieve a particular feed without the supplier knowing which feed you actually got, and Symmetric Private Information Retrieval (SPIR) will assure the supplier, if the feeds are equally priced, that you received only the number of feeds you purchased. Now you can purchase without risking your name being associated with a particular feed and the supplier has gained the business of a once paranoid client. The problem of SPIR can be achieved with the cryptographic primitive Oblivious Transfer (OT). Several approaches to constructing such protocols have been posed and proven to be secure. Most attempts have aimed at reducing the amount of communication, theoretically, but this thesis compares the computational expense of the algorithms through experimentation to show that reduction of communication is less valuable in the effort of achieving a practical protocol than reducing the amount of computation. Further...

Introducción: Aborda la utilización de los sintagmas nominales en el proceso de indización automática de las tesis y las disertaciones depositadas en la Biblioteca Digital de Tesis y Disertaciones de UFPE (BDTD-UFPE), considerando la hipótesis de que los sintagmas nominales consistirían en una mejor unidad de conocimiento para la indización y recuperación de información, que términos aislados, permitiendo aumentar la satisfacción de las necesidades de información del usuario durante la búsqueda de información. Se discute sobre el estado del arte de los sintagmas nominales y de su extracción automática, tanto como de su aplicación en la indización automática y en la recuperación de información. Metodología: Tomando como base la herramienta para análisis de texto (OGMA), analiza la aplicación de la extracción de sintagmas nominales en la indización automática y recuperación de información de las tesis y disertaciones en el contexto de BDTD-UFPE. Con base en los resúmenes en el área de Derecho, Computación y Nutrición, se definieron los valores totales para cada una de las variables observadas, lo que permitió evaluar la extracción de sintagmas nominales a través de los porcentajes de precisión de los sintagmas nominales relevantes; la tasa de error al extraer las cadenas de caracteres que no constituyen sintagmas nominales...