1,476 research outputs found

    Sharing Semantic Resources

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    The Semantic Web is an extension of the current Web in which information, so far created for human consumption, becomes machine readable, “enabling computers and people to work in cooperation”. To turn into reality this vision several challenges are still open among which the most important is to share meaning formally represented with ontologies or more generally with semantic resources. This Semantic Web long-term goal has many convergences with the activities in the field of Human Language Technology and in particular in the development of Natural Language Processing applications where there is a great need of multilingual lexical resources. For instance, one of the most important lexical resources, WordNet, is also commonly regarded and used as an ontology. Nowadays, another important phenomenon is represented by the explosion of social collaboration, and Wikipedia, the largest encyclopedia in the world, is object of research as an up to date omni comprehensive semantic resource. The main topic of this thesis is the management and exploitation of semantic resources in a collaborative way, trying to use the already available resources as Wikipedia and Wordnet. This work presents a general environment able to turn into reality the vision of shared and distributed semantic resources and describes a distributed three-layer architecture to enable a rapid prototyping of cooperative applications for developing semantic resources

    Query Expansion using LMF-Compliant Lexical Resources

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    This paper reports prototype multilingual query expansion system relying on LMF compliant lexical resources. The system is one of the deliverables of a three-year project aiming at establishing an international standard for language resources which is applicable to Asian languages. Our important contributions to ISO 24613, standard Lexical Markup Framework (LMF) include its robustness to deal with Asian languages, and its applicability to cross-lingual query tasks, as illustrated by the prototype introduced in this paper

    The Digital Classicist 2013

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    This edited volume collects together peer-reviewed papers that initially emanated from presentations at Digital Classicist seminars and conference panels. This wide-ranging volume showcases exemplary applications of digital scholarship to the ancient world and critically examines the many challenges and opportunities afforded by such research. The chapters included here demonstrate innovative approaches that drive forward the research interests of both humanists and technologists while showing that rigorous scholarship is as central to digital research as it is to mainstream classical studies. As with the earlier Digital Classicist publications, our aim is not to give a broad overview of the field of digital classics; rather, we present here a snapshot of some of the varied research of our members in order to engage with and contribute to the development of scholarship both in the fields of classical antiquity and Digital Humanities more broadly

    The Digital Classicist 2013

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    This edited volume collects together peer-reviewed papers that initially emanated from presentations at Digital Classicist seminars and conference panels. This wide-ranging volume showcases exemplary applications of digital scholarship to the ancient world and critically examines the many challenges and opportunities afforded by such research. The chapters included here demonstrate innovative approaches that drive forward the research interests of both humanists and technologists while showing that rigorous scholarship is as central to digital research as it is to mainstream classical studies. As with the earlier Digital Classicist publications, our aim is not to give a broad overview of the field of digital classics; rather, we present here a snapshot of some of the varied research of our members in order to engage with and contribute to the development of scholarship both in the fields of classical antiquity and Digital Humanities more broadly

    Ontologies on the semantic web

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    As an informational technology, the World Wide Web has enjoyed spectacular success. In just ten years it has transformed the way information is produced, stored, and shared in arenas as diverse as shopping, family photo albums, and high-level academic research. The “Semantic Web” was touted by its developers as equally revolutionary but has not yet achieved anything like the Web’s exponential uptake. This 17 000 word survey article explores why this might be so, from a perspective that bridges both philosophy and IT

    A common ground for virtual humans: using an ontology in a natural language oriented virtual human architecture

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    When dealing with large, distributed systems that use state-of-the-art components, individual components are usually developed in parallel. As development continues, the decoupling invariably leads to a mismatch between how these components internally represent concepts and how they communicate these representations to other components: representations can get out of synch, contain localized errors, or become manageable only by a small group of experts for each module. In this paper, we describe the use of an ontology as part of a complex distributed virtual human architecture in order to enable better communication between modules while improving the overall flexibility needed to change or extend the system. We focus on the natural language understanding capabilities of this architecture and the relationship between language and concepts within the entire system in general and the ontology in particular. 1

    Natural language processing

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    Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems

    Advanced Knowledge Technologies at the Midterm: Tools and Methods for the Semantic Web

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    The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprints and on-line copies for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are the author’s and shouldn’t be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of other parties.In a celebrated essay on the new electronic media, Marshall McLuhan wrote in 1962:Our private senses are not closed systems but are endlessly translated into each other in that experience which we call consciousness. Our extended senses, tools, technologies, through the ages, have been closed systems incapable of interplay or collective awareness. Now, in the electric age, the very instantaneous nature of co-existence among our technological instruments has created a crisis quite new in human history. Our extended faculties and senses now constitute a single field of experience which demands that they become collectively conscious. Our technologies, like our private senses, now demand an interplay and ratio that makes rational co-existence possible. As long as our technologies were as slow as the wheel or the alphabet or money, the fact that they were separate, closed systems was socially and psychically supportable. This is not true now when sight and sound and movement are simultaneous and global in extent. (McLuhan 1962, p.5, emphasis in original)Over forty years later, the seamless interplay that McLuhan demanded between our technologies is still barely visible. McLuhan’s predictions of the spread, and increased importance, of electronic media have of course been borne out, and the worlds of business, science and knowledge storage and transfer have been revolutionised. Yet the integration of electronic systems as open systems remains in its infancy.Advanced Knowledge Technologies (AKT) aims to address this problem, to create a view of knowledge and its management across its lifecycle, to research and create the services and technologies that such unification will require. Half way through its sixyear span, the results are beginning to come through, and this paper will explore some of the services, technologies and methodologies that have been developed. We hope to give a sense in this paper of the potential for the next three years, to discuss the insights and lessons learnt in the first phase of the project, to articulate the challenges and issues that remain.The WWW provided the original context that made the AKT approach to knowledge management (KM) possible. AKT was initially proposed in 1999, it brought together an interdisciplinary consortium with the technological breadth and complementarity to create the conditions for a unified approach to knowledge across its lifecycle. The combination of this expertise, and the time and space afforded the consortium by the IRC structure, suggested the opportunity for a concerted effort to develop an approach to advanced knowledge technologies, based on the WWW as a basic infrastructure.The technological context of AKT altered for the better in the short period between the development of the proposal and the beginning of the project itself with the development of the semantic web (SW), which foresaw much more intelligent manipulation and querying of knowledge. The opportunities that the SW provided for e.g., more intelligent retrieval, put AKT in the centre of information technology innovation and knowledge management services; the AKT skill set would clearly be central for the exploitation of those opportunities.The SW, as an extension of the WWW, provides an interesting set of constraints to the knowledge management services AKT tries to provide. As a medium for the semantically-informed coordination of information, it has suggested a number of ways in which the objectives of AKT can be achieved, most obviously through the provision of knowledge management services delivered over the web as opposed to the creation and provision of technologies to manage knowledge.AKT is working on the assumption that many web services will be developed and provided for users. The KM problem in the near future will be one of deciding which services are needed and of coordinating them. Many of these services will be largely or entirely legacies of the WWW, and so the capabilities of the services will vary. As well as providing useful KM services in their own right, AKT will be aiming to exploit this opportunity, by reasoning over services, brokering between them, and providing essential meta-services for SW knowledge service management.Ontologies will be a crucial tool for the SW. The AKT consortium brings a lot of expertise on ontologies together, and ontologies were always going to be a key part of the strategy. All kinds of knowledge sharing and transfer activities will be mediated by ontologies, and ontology management will be an important enabling task. Different applications will need to cope with inconsistent ontologies, or with the problems that will follow the automatic creation of ontologies (e.g. merging of pre-existing ontologies to create a third). Ontology mapping, and the elimination of conflicts of reference, will be important tasks. All of these issues are discussed along with our proposed technologies.Similarly, specifications of tasks will be used for the deployment of knowledge services over the SW, but in general it cannot be expected that in the medium term there will be standards for task (or service) specifications. The brokering metaservices that are envisaged will have to deal with this heterogeneity.The emerging picture of the SW is one of great opportunity but it will not be a wellordered, certain or consistent environment. It will comprise many repositories of legacy data, outdated and inconsistent stores, and requirements for common understandings across divergent formalisms. There is clearly a role for standards to play to bring much of this context together; AKT is playing a significant role in these efforts. But standards take time to emerge, they take political power to enforce, and they have been known to stifle innovation (in the short term). AKT is keen to understand the balance between principled inference and statistical processing of web content. Logical inference on the Web is tough. Complex queries using traditional AI inference methods bring most distributed computer systems to their knees. Do we set up semantically well-behaved areas of the Web? Is any part of the Web in which semantic hygiene prevails interesting enough to reason in? These and many other questions need to be addressed if we are to provide effective knowledge technologies for our content on the web

    Language technologies for a multilingual Europe

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    This volume of the series “Translation and Multilingual Natural Language Processing” includes most of the papers presented at the Workshop “Language Technology for a Multilingual Europe”, held at the University of Hamburg on September 27, 2011 in the framework of the conference GSCL 2011 with the topic “Multilingual Resources and Multilingual Applications”, along with several additional contributions. In addition to an overview article on Machine Translation and two contributions on the European initiatives META-NET and Multilingual Web, the volume includes six full research articles. Our intention with this workshop was to bring together various groups concerned with the umbrella topics of multilingualism and language technology, especially multilingual technologies. This encompassed, on the one hand, representatives from research and development in the field of language technologies, and, on the other hand, users from diverse areas such as, among others, industry, administration and funding agencies. The Workshop “Language Technology for a Multilingual Europe” was co-organised by the two GSCL working groups “Text Technology” and “Machine Translation” (http://gscl.info) as well as by META-NET (http://www.meta-net.eu)

    Lexicons and grammars for language processing: industrial or handcrafted products?

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    Lexicon and Grammar: From Meanings to the Construction of SignificationDuring the recent years, the use of linguistic data for language processing (semantic ambiguityresolution, translation...) increased progressively. Such data are now commonly called languageresources. A few years ago, nearly all the language resources used for this purpose were collectionsof texts as the Brown Corpus and the Penn Treebank, but the use of electronic lexicons (WordNet,FrameNet, VerbNet, ComLex, Lexicon-Grammar...) and formal grammars (TAG...) developed recently. Thisdevelopment is slow because most processes of construction of lexicons and grammars aremanual, whereas the construction of corpora has always been highly automated.However, more and more specialists of language processing realize that the information content oflexicons and grammars is richer than that of corpora, and hence the former make more elaborateprocessing possible. The difference in construction time is likely to be connected with thedifference in information content: the handcrafting of lexicons and grammars by linguists wouldmake them more informative than automatically generated data.This situation can evolve into two directions: either specialists of language technology getprogressively used to handling manually constructed resources, which are more informative andmore complex, or the process of construction of lexicons and grammars is automated andindustrialized, which is the mainstream perspective. Both evolutions are already in progress, and atension exists between them. The relation between linguists and computer scientists depends on thefuture of these evolutions, since the first implies training and hiring numerous linguists, whereasthe other depends essentially on solutions elaborated by computer engineers.The aim of this article is to analyse practical examples of the language resources in question, andto discuss about which of the two trends, handcrafting or generating industrially, or a combinationof both, can give the best results or is the most realistic.L'utilisation de donnĂ©es linguistiques pour le traitement des langues : levĂ©e d'ambiguĂŻtĂ©s sĂ©mantiques, traduction... a augmentĂ© progressivement au cours des derniĂšres annĂ©es. De telles donnĂ©es sont communĂ©ment appelĂ©es ressources linguistiques. Il y a quelques annĂ©es, presque toutes les ressources linguistiques exploitĂ©es pour ce type d'usage Ă©taient des collections de textes telles que le Corpus de Brown et le Corpus arborĂ© de Penn, mais l'utilisation de lexiques Ă©lectroniques (WordNet, FrameNet, VerbNet, ComLex, Lexique-Grammaire...) et de grammaires formelles (grammaires d'adjonction d'arbres...) s'est dĂ©veloppĂ© depuis. Cet essor est lent, car la plupart des processus de construction de lexiques et de grammaires sont manuels, alors que la construction de corpus a Ă©tĂ© trĂšs tĂŽt en grande partie automatisĂ©e. Cependant, de plus en plus de spĂ©cialistes du traitement des langues jugent le contenu informatif des lexiques et des grammaires plus riche que celui des corpus, ce qui ouvre la possibilitĂ© de traitements plus Ă©laborĂ©s. La diffĂ©rence dans la durĂ©e de construction de ces deux types de ressources est sans doute liĂ©e Ă  la diffĂ©rence de richesse du contenu informatif : la construction artisanale de lexiques et de grammaires par les linguistes les rendrait plus informatifs que des donnĂ©es engendrĂ©es automatiquement.Cette situation peut Ă©voluer dans deux directions : ou les spĂ©cialistes de technologie linguistique se familiarisent progressivement avec la manipulation de ressources construites manuellement, plus informatives et plus complexes, ou les processus de construction de lexiques et de grammaires sont automatisĂ©s et industrialisĂ©s, ce qui est la perspective la plus rĂ©pandue.Les deux Ă©volutions sont dĂ©jĂ  Ă  l'Ɠuvre, et il existe une tension entre elles deux. Les relations entre linguistes et informaticiens dĂ©pendent du futur de ces Ă©volutions, puisque celle-lĂ  suppose la formation et le recrutement de nombreux linguistes, alors que celle-ci dĂ©pend essentiellement de solutions Ă©laborĂ©es par des ingĂ©nieurs de l'informatique.Le but de cet article est d'analyser des exemples pratiques des ressources linguistiques en question, et de discuter sur la question de savoir laquelle des deux tendances, l'artisanale ou l'industrielle, ou une combinaison des deux, pourrait donner les meilleurs rĂ©sultats ou s'avĂ©rer la plus rĂ©aliste
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