63 research outputs found

    Ontology-Based Interactive Information Extraction From Scientific Abstracts

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    Over recent years, there has been a growing interest in extracting information automatically or semi-automatically from the scientific literature. This paper describes a novel ontology-based interactive information extraction (OBIIE) framework and a specific OBIIE system. We describe how this system enables life scientists to make ad hoc queries similar to using a standard search engine, but where the results are obtained in a database format similar to a pre-programmed information extraction engine. We present a case study in which the system was evaluated for extracting co-factors from EMBASE and MEDLINE

    Towards a killer app for the Semantic Web

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    Killer apps are highly transformative technologies that create new markets and widespread patterns of behaviour. IT generally, and the Web in particular, has benefited from killer apps to create new networks of users and increase its value. The Semantic Web community on the other hand is still awaiting a killer app that proves the superiority of its technologies. There are certain features that distinguish killer apps from other ordinary applications. This paper examines those features in the context of the Semantic Web, in the hope that a better understanding of the characteristics of killer apps might encourage their consideration when developing Semantic Web applications

    Simplifying syntactic and semantic parsing of NL-based queries in advanced application domains

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    The paper presents a high level query language (MDDQL) for databases, which relies on an ontology driven automaton. This is simulated by the human-computer interaction mode for the query construction process, which is driven by an inference engine operating upon a frames based ontology description. Therefore, given that the query construction process implicitly leads to the contemporary construction of high level query trees prior to submission of the query for transformation and execution to a semantic middle-ware, syntactic and semantic parsing of a query with conventional techniques, i.e., after completion of its formulation, becomes obsolete. To this extent, only, as meaningful as possible, queries can be constructed at a low typing, learning, syntactic and semantic parsing effort and regardless the preferred natural (sub)language. From a linguistics point o view, it turns out that the query construction mechanism can easily be adapted and work with families of natural languages, which underlie another type order such as Subject-Object-Verb as opposed to the typical Subject-Verb-Object type order, which underlie most European languages. The query construction mechanism has been proved as practical in advanced application domains, such as those provided by medical applications, with an advanced and hardly understood terminology for naive users and the public

    Topic Maps : a bibliometric study

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    Topic Maps is an international standard (ISO/IEC 13250) to describe and encode knowledge structures and associating them with relevant information resources. This thesis seeks to investigate what has been written about Topic Maps from year 2000 to 2011, as well as finding out the research and publication trend in Topic Maps. This study was based on quantitative methodology, which was bibliometric analysis. The data was collected from Scopus and Web of Knowledge databases. Search keywords used are “topic map”, “topic maps” and “ISO/IEC 13250”. A total of 356 publications (265 conference papers, 91 journal articles) from 2001 to 2011 taken into data analysis. The findings revealed that Topic Maps researchers had a preference to present their findings in conference rather than in journal. The authorship pattern was more towards coauthorship. Most researchers were coauthored locally, as international collaboration was very low. Computer science and library and information science related journals were the favourite publishing venue. Majority of the conferences were computer science and education related. The focus of the topic maps was on data integration and interoperability (2001-2004), information theory (2005 – 2008), knowledge and intelligent based system (2009 – 2011). Also, there were five themes identified, namely content management, repository, ontology, information architecture, retrieval and navigation, and semantic web. The future research areas will possibly be collaborative e-learning system, knowledge visualization system, visualization construction, semantic metadata creation from a relational database, knowledge navigation and retrieval improvement, intelligent topic map, distributed knowledge management based on extended topic maps, knowledge service system, knowledge representation modeling, and multi granularity and multi-level knowledge.Joint Master Degree in Digital Library Learning (DILL

    Semi-Automated Development of Conceptual Models from Natural Language Text

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    The process of converting natural language specifications into conceptual models requires detailed analysis of natural language text, and designers frequently make mistakes when undertaking this transformation manually. Although many approaches have been used to help designers translate natural language text into conceptual models, each approach has its limitations. One of the main limitations is the lack of a domain-independent ontology that can be used as a repository for entities and relationships, thus guiding the transition from natural language processing into a conceptual model. Such an ontology is not currently available because it would be very difficult and time consuming to produce. In this thesis, a semi-automated system for mapping natural language text into conceptual models is proposed. The model, which is called SACMES, combines a linguistic approach with an ontological approach and human intervention to achieve the task. The model learns from the natural language specifications that it processes, and stores the information that is learnt in a conceptual model ontology and a user history knowledge database. It then uses the stored information to improve performance and reduce the need for human intervention. The evaluation conducted on SACMES demonstrates that (1) designers’ creation of conceptual models is improved when using the system comparing with not using any system, and that (2) the performance of the system is improved by processing more natural language requirements, and thus, the need for human intervention has decreased. However, these advantages may be improved further through development of the learning and retrieval techniques used by the system

    SWA-KMDLS: An Enhanced e-Learning Management System Using Semantic Web and Knowledge Management Technology

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    In this era of knowledge economy in which knowledge have become the most precious resource, surveys have shown that e-Learning has been on the increasing trend in various organizations including, among others, education and corporate. The use of e-Learning is not only aim to acquire knowledge but also to maintain competitiveness and advantages for individuals or organizations. However, the early promise of e-Learning has yet to be fully realized, as it has been no more than a handout being published online, coupled with simple multiple-choice quizzes. The emerging of e-Learning 2.0 that is empowered by Web 2.0 technology still hardly overcome common problem such as information overload and poor content aggregation in a highly increasing number of learning objects in an e-Learning Management System (LMS) environment. The aim of this research study is to exploit the Semantic Web (SW) and Knowledge Management (KM) technology; the two emerging and promising technology to enhance the existing LMS. The proposed system is named as Semantic Web Aware-Knowledge Management Driven e-Learning System (SWA-KMDLS). An Ontology approach that is the backbone of SW and KM is introduced for managing knowledge especially from learning object and developing automated question answering system (Aquas) with expert locator in SWA-KMDLS. The METHONTOLOGY methodology is selected to develop the Ontology in this research work. The potential of SW and KM technology is identified in this research finding which will benefit e-Learning developer to develop e-Learning system especially with social constructivist pedagogical approach from the point of view of KM framework and SW environment. The (semi-) automatic ontological knowledge base construction system (SAOKBCS) has contributed to knowledge extraction from learning object semiautomatically whilst the Aquas with expert locator has facilitated knowledge retrieval that encourages knowledge sharing in e-Learning environment. The experiment conducted has shown that the SAOKBCS can extract concept that is the main component of Ontology from text learning object with precision of 86.67%, thus saving the expert time and effort to build Ontology manually. Additionally the experiment on Aquas has shown that more than 80% of users are satisfied with answers provided by the system. The expert locator framework can also improve the performance of Aquas in the future usage. Keywords: semantic web aware – knowledge e-Learning Management System (SWAKMDLS), semi-automatic ontological knowledge base construction system (SAOKBCS), automated question answering system (Aquas), Ontology, expert locator

    From Signal to Social : Steps Towards Pervasive Social Context

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    The widespread adoption of smartphones with advanced sensing, computing and data transfer capabilities has made scientific studies of human social behavior possible at a previously unprecedented scale. It has also allowed context-awareness to become a natural feature in many applications using features such as activity recognition and location information. However, one of the most important aspects of context remains largely untapped at scale, i.e. social interactions and social context. Social interaction sensing has been explored using smartphones and specialized hardware for research purposes within computational social science and ubiquitous computing, but several obstacles remain to make it usable in practice by applications at industrial scale. In this thesis, I explore methods of physical proximity sensing and extraction of social context information from user-generated data for the purpose of context-aware applications. Furthermore, I explore the application space made possible through these methods, especially in the class of use cases that are characterized by embodied social agency, through field studies and a case study.A major concern when collecting context information is the impact on user privacy. I have performed a user study in which I have surveyed the user attitudes towards the privacy implications of proximity sensing. Finally, I present results from quantitatively estimating the sensitivity of a simple type of context information, i.e. application usage, in terms of risk of user re-identification

    Linguistic-based Patterns for Figurative Language Processing: The Case of Humor Recognition and Irony Detection

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    El lenguaje figurado representa una de las tareas más difíciles del procesamiento del lenguaje natural. A diferencia del lenguaje literal, el lenguaje figurado hace uso de recursos lingüísticos tales como la ironía, el humor, el sarcasmo, la metáfora, la analogía, entre otros, para comunicar significados indirectos que la mayoría de las veces no son interpretables sólo en términos de información sintáctica o semántica. Por el contrario, el lenguaje figurado refleja patrones del pensamiento que adquieren significado pleno en contextos comunicativos y sociales, lo cual hace que tanto su representación lingüística, así como su procesamiento computacional, se vuelvan tareas por demás complejas. En este contexto, en esta tesis de doctorado se aborda una problemática relacionada con el procesamiento del lenguaje figurado a partir de patrones lingüísticos. En particular, nuestros esfuerzos se centran en la creación de un sistema capaz de detectar automáticamente instancias de humor e ironía en textos extraídos de medios sociales. Nuestra hipótesis principal se basa en la premisa de que el lenguaje refleja patrones de conceptualización; es decir, al estudiar el lenguaje, estudiamos tales patrones. Por tanto, al analizar estos dos dominios del lenguaje figurado, pretendemos dar argumentos respecto a cómo la gente los concibe, y sobre todo, a cómo esa concepción hace que tanto humor como ironía sean verbalizados de una forma particular en diversos medios sociales. En este contexto, uno de nuestros mayores intereses es demostrar cómo el conocimiento que proviene del análisis de diferentes niveles de estudio lingüístico puede representar un conjunto de patrones relevantes para identificar automáticamente usos figurados del lenguaje. Cabe destacar que contrario a la mayoría de aproximaciones que se han enfocado en el estudio del lenguaje figurado, en nuestra investigación no buscamos dar argumentos basados únicamente en ejemplos prototípicos, sino en textos cuyas característicasReyes Pérez, A. (2012). Linguistic-based Patterns for Figurative Language Processing: The Case of Humor Recognition and Irony Detection [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/16692Palanci

    Nodalida 2005 - proceedings of the 15th NODALIDA conference

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    Semi-automatic wrapper generation for semi-structured websites

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    Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.Includes bibliographical references (leaves 69-74).Many information sources on the Web are semi-structured; hence there is an opportunity for automatic tools to process and extract their information for easy access through a uniform interface language. Wrapper generation is the creation of wrappers which contains scripts that extract and integrate data from data sources, mostly from Web data sources due to the large amount of data available on the World Wide Web. Despite ongoing efforts to automate the process of wrapper generation, wrappers frequently break due to formatting and layout changes in data sources. This thesis presents Wrapster, a new system that semi-automatically generates wrappers for semi-structured Web sources, improves wrapper robustness, and eliminates the need for programming skills and, to a large extent, the process of script creation. Wrapster's novel component is the repairing module that constantly checks if any wrapper script has failed and repairs the failing wrapper's script using stored extracted instances. In addition, Wrapster provides an interactive Web user interface to control the wrapper generation process, edit the generated wrappers, and test their scripts. Wrapster is being tested on the START Question Answering system; however, it is a generic tool to be used by any QA system that uses the Web as its knowledge base.by Gabriel Zaccak.S.M
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