3,589 research outputs found

    Mining Domain-Specific Thesauri from Wikipedia: A case study

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    Domain-specific thesauri are high-cost, high-maintenance, high-value knowledge structures. We show how the classic thesaurus structure of terms and links can be mined automatically from Wikipedia. In a comparison with a professional thesaurus for agriculture we find that Wikipedia contains a substantial proportion of its concepts and semantic relations; furthermore it has impressive coverage of contemporary documents in the domain. Thesauri derived using our techniques capitalize on existing public efforts and tend to reflect contemporary language usage better than their costly, painstakingly-constructed manual counterparts

    From Frequency to Meaning: Vector Space Models of Semantics

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    Computers understand very little of the meaning of human language. This profoundly limits our ability to give instructions to computers, the ability of computers to explain their actions to us, and the ability of computers to analyse and process text. Vector space models (VSMs) of semantics are beginning to address these limits. This paper surveys the use of VSMs for semantic processing of text. We organize the literature on VSMs according to the structure of the matrix in a VSM. There are currently three broad classes of VSMs, based on term-document, word-context, and pair-pattern matrices, yielding three classes of applications. We survey a broad range of applications in these three categories and we take a detailed look at a specific open source project in each category. Our goal in this survey is to show the breadth of applications of VSMs for semantics, to provide a new perspective on VSMs for those who are already familiar with the area, and to provide pointers into the literature for those who are less familiar with the field

    Towards Affordable Disclosure of Spoken Word Archives

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    This paper presents and discusses ongoing work aiming at affordable disclosure of real-world spoken word archives in general, and in particular of a collection of recorded interviews with Dutch survivors of World War II concentration camp Buchenwald. Given such collections, the least we want to be able to provide is search at different levels and a flexible way of presenting results. Strategies for automatic annotation based on speech recognition – supporting e.g., within-document search– are outlined and discussed with respect to the Buchenwald interview collection. In addition, usability aspects of the spoken word search are discussed on the basis of our experiences with the online Buchenwald web portal. It is concluded that, although user feedback is generally fairly positive, automatic annotation performance is still far from satisfactory, and requires additional research

    Web based knowledge extraction and consolidation for automatic ontology instantiation

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    The Web is probably the largest and richest information repository available today. Search engines are the common access routes to this valuable source. However, the role of these search engines is often limited to the retrieval of lists of potentially relevant documents. The burden of analysing the returned documents and identifying the knowledge of interest is therefore left to the user. The Artequakt system aims to deploy natural language tools to automatically ex-tract and consolidate knowledge from web documents and instantiate a given ontology, which dictates the type and form of knowledge to extract. Artequakt focuses on the domain of artists, and uses the harvested knowledge to gen-erate tailored biographies. This paper describes the latest developments of the system and discusses the problem of knowledge consolidation

    Automatic metadata generation in an archaeological digital library: Semantic annotation of grey literature

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    . This paper discusses the automatic generation of rich metadata from excavation reports from the Archaeological Data Service library of grey literature (OASIS). The work is part of the STAR project, in collaboration with English Heritage. An extension of the CIDOC CRM ontology for the archaeological domain acts as a core ontology. Rich metadata is automatically extracted from grey literature, directed by the CRM, via a three phase process of semantic enrichment employing the GATE toolkit augmented with bespoke rules and knowledge resources. The paper demonstrates the potential of combining knowledge based resources (ontologies and thesauri) in information extraction, and techniques for delivering the automatically extracted metadata as XML annotations coupled with the grey literature reports and as RDF graphs decoupled from content. Examples from two consuming applications are discussed, the Andronikos web portal which serves the annotated XML files for visual inspection and the STAR project, research demonstrator which offers unified search across of archaeological excavation data and grey literature via the core ontology CRM-EH

    Design of a Controlled Language for Critical Infrastructures Protection

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    We describe a project for the construction of controlled language for critical infrastructures protection (CIP). This project originates from the need to coordinate and categorize the communications on CIP at the European level. These communications can be physically represented by official documents, reports on incidents, informal communications and plain e-mail. We explore the application of traditional library science tools for the construction of controlled languages in order to achieve our goal. Our starting point is an analogous work done during the sixties in the field of nuclear science known as the Euratom Thesaurus.JRC.G.6-Security technology assessmen

    Onto.PT: Automatic Construction of a Lexical Ontology for Portuguese

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    This ongoing research presents an alternative to the man- ual creation of lexical resources and proposes an approach towards the automatic construction of a lexical ontology for Portuguese. Tex- tual sources are exploited in order to obtain a lexical network based on terms and, after clustering and mapping, a wordnet-like lexical on- tology is created. At the end of the paper, current results are shown
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