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Ontology for semantic representation of marine metadata 13

Ontology for semantic representation of marine metadata

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7th international conference on Ubiquitous information Management and Communication, ICUIMC 2013

作者： Park, DaeWon Kwon, Hyuk-Chul Park, Suhyun Dept. of Computer Science and Engineering Pusan National University Busandaehak-ro 63 Geumjung-gu Busan 609-735 Korea Republic of Division of Computer and Information Engineering Dongseo University Jurye-ro 4 Sasang-gu Busan 609-716 Korea Republic of

ISBN: (纸本)9781450319584

Metadata provides the information that describes, explains, or makes it easier to retrieve, use, or manage information resources. In the marine field, a metadata model is defined and used for exchange, retrieval, integration, and usage of data, such as hydrographic data. the S-100 of the international Hydrographic Organization (IHO), recently introduced new paradigm for integration and usage of various data on marine safety and the marine environment, also includes a metadata model defined in uniformed modeling language (UML). this model, consisting of entities that describe the main concepts and conceptual structures of metadata, provides for syntactic interoperability between systems. However, semantic heterogeneities as well as difficulties encountered in automatic semantic-based processing remain yet. For the purposes of enhancing semantic interoperability between systems on the S-100-based infrastructure, we herein introduce a new metadata ontology. Analyzing metadata elements in the S- 100 metadata model, we removed the syntactic and semantic redundancies of the metadata elements. After conceptualizing and generalizing the metadata elements, we defined ontology elements free of syntactic or semantic redundancy. Additionally, we improved the previous ontology by UML-to-OWL conversion. Copyright © 2013 ACM.

关键词： Metadata

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Multi-level architecture on web services based policy domain use cases simulator 9th

Multi-level architecture on web services based policy domain...

引用

9th international Workshop on Enterprise and Organizational Modeling and Simulation, EOMAS 2013, Held in Conjunction with 25th conference on advanced information Systems Engineering, CAiSE 2013

作者： Aizstrauts, Artis Ginters, Egils Lauberte, Ieva Eroles, Miquel Angel Piera Sociotechnical Systems Engineering Institute Vidzeme University of Applied Sciences Valmiera Latvia Dept. de Telecomunicació i Enginyeria de Sistemes Universitat Autònoma de Barcelona Barcelona Spain

ISBN: (纸本)9783642416378

the FP7 FUPOL project aims at a completely new approach to traditional policy modeling providing complex domain use case verification with the FUPOL Simulator and visualisation of the results in a form suitable for beneficiaries. Policy domain use case models are diverse and versatile, therefore architecture of the simulator must fit complexity and usability requirements that determine involving heterogeneous agent-based and system dynamics simulation technologies and an appropriate implementation comprising on SOA based distributed models joined by Easy Communication Environment (ECE). the article deals with designing the FUPOL Simulator architecture, and the benefits, and drawbacks of the approach used. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Simulators

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Developing text and speech databases for speech recognition of Vietnamese

Developing text and speech databases for speech recognition ...

引用

IEEE international Workshop on Intelligent Data Acquisition and advanced Computing Systems: technology and Applications

作者： Nguyen thien Chuong Josef Chaloupka Technical University of Liberec Institute of Information Technology and Electronics Czech Republic

this paper describes our study on developing the text and speech databases for automatic speech recognition of Vietnamese using an available source of linguistic data: the Internet. First, a two-stage procedure is applied to extract a general text corpus which can be used for researches on Vietnamese language such as speech recognition, audio-visual speech recognition, and natural language processing... We also collect another specific text corpus in the field of news and literature using the resource from some main web sites of Vietnamese. the total text corpus containing 8,681,869 sentences with more than 124 million syllables is then used to build and test the language model for the speech recognizer. Besides, the collecting of speech corpora for experiments on continuous speech recognition and audio-visual speech recognition of Vietnamese are also described.

关键词： Speech Speech recognition Internet Vocabulary Encyclopedias Electronic publishing

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A prototype application for real-time recognition and disambiguation of clinical abbreviations

A prototype application for real-time recognition and disamb...

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7th ACM international Workshop on Data and Text Mining in Biomedical Informatics, DTMBIO 2013, in Conjunction with the 22nd ACM international conference on information and Knowledge Management, CIKM 2013

作者： Wu, Yonghui Denny, Joshua C. Rosenbloom, S. Trent Miller, Randolph A. Giuse, Dario A. Song, Min Xu, Hua School of Biomedical Informatics University of Texas Health Science Center at Houston Houston TX United States Department of Biomedical Informatics Vanderbilt University Nashville TN United States Department of Library and Information Science Yonsei University Seoul Korea Republic of

ISBN: (纸本)9781450324199

To save time, healthcare providers frequently use abbreviations while authoring clinical documents. Nevertheless, abbreviations that authors deem unambiguous often confuse other readers, including clinicians, patients, and natural language processing (NLP) systems. Most current clinical NLP systems "post-process" notes long after clinicians enter them into electronic health record systems (EHRs). Such post-processing cannot guarantee 100% accuracy in abbreviation identification and disambiguation, since multiple alternative interpretations exist. In this paper, authors describe a prototype system for real-time Clinical Abbreviation Recognition and Disambiguation (CARD) - i.e., a system that interacts with authors during note generation to verify correct abbreviation senses. the CARD system design anticipates future integration with web-based clinical documentation systems to improve quality of healthcare records. the prototype application embodies three word sense disambiguation (WSD) methods. We evaluated the accuracy and response times of the prototype CARD system in a simulated study. Using an existing test data set of 25 commonly observed, highly ambiguous clinical abbreviations the evaluation demonstrated that the best WSD method had an accuracy of 88.8%, and a reasonable average response time of 1.6 milliseconds per each abbreviation. the study indicates potential feasibility of real-time NLP-enabled abbreviation disambiguation within clinical documentation systems. Copyright © 2013 ACM.

关键词： Natural language processing systems

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web-based notation of mathematical text preserving semantics for scientific and educational communication

Web-based notation of mathematical text preserving semantics...

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IEEE international Workshop on Intelligent Data Acquisition and advanced Computing Systems: technology and Applications

作者： Anatolii Vovk Denys Girnyk State Research Institute of Automated Systems in Construction Kyiv Ukraine International Research and Training Center for Information Technologies and Systems Kyiv Ukraine

the present paper deals with web-based notation, which implements a natural language representation of mathematical texts and preserves their semantics. We have developed a visualization of notation for browsers and its export to standard formats TeX, Content MathML and PDF. the suggested web-notation provides interactive communication over the Internet, as well as compatibility and interoperability of prepared texts in other applications.

关键词： Internet Semantics Mathematics Browsers Visualization Computer languages Standards

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Effective Selectional Restrictions for Unsupervised Relation Extraction 6

Effective Selectional Restrictions for Unsupervised Relation...

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6th international Joint conference on Natural language processing, IJCNLP 2013

作者： Akbik, Alan Visengeriyeva, Larysa Kirschnick, Johannes Löser, Alexander Technische Univeristät Berlin Databases and Information Systems Group Einsteinufer 17 Berlin10587 Germany

ISBN: (纸本)9784990734800

Unsupervised Relation Extraction (URE) methods automatically discover semantic relations in text corpora of unknown content and extract for each discovered relation a set of relation instances. Due to the sparsity of the feature space, URE is vulnerable to ambiguities and underspecification in patterns. In this paper, we propose to increase the discriminative power of patterns in URE using selectional restrictions (SR). We propose a method that utilizes a web-derived soft clustering of n-grams to model selectional restrictions in the open domain. We comparatively evaluate our method against a baseline without SR, a setup in which standard 7-class Named Entity types are used as SR and a setup that models SR using a fine-grained entity type system. Our results indicate that modeling SR into patterns significantly improves the ability of URE to discover relations and enables the discovery of more fine-granular relations. © IJCNLP *** right reserved.

关键词： Extraction

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Bayesian Induction of Bracketing Inversion Transduction Grammars 6

Bayesian Induction of Bracketing Inversion Transduction Gram...

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6th international Joint conference on Natural language processing, IJCNLP 2013

作者： Saers, Markus Wu, Dekai Human Language Technology Center Department of Computer Science and Engineering Hong Kong University of Science and Technology

ISBN: (纸本)9784990734800

We present a novel approach to learning phrasal inversion transduction grammars via Bayesian MAP (maximum a posteriori) or information-theoretic MDL (minimum description length) model optimization so as to incorporate simultaneously the choices of model structure as well as parameters. In comparison to most current SMT approaches, the model learns phrase translation lexicons that (a) do not require enormous amounts of run-time memory, (b) contain significantly less redundancy, and (c) provide an obvious basis for generalization to abstract translation schemas. Model structure choice is biased by a description length prior, while parameter choice is driven by data likelihood biased by a parameter prior. the search over possible model structures is made feasible by a novel top-down rule segmenting heuristic which efficiently incorporates estimates of the posterior probabilities. Since the priors reward model parsimony, the learned grammar is very concise and still performs significantly better than the maximum likelihood driven bottom-up rule chunking baseline. © IJCNLP *** right reserved.

关键词： Bacteriophages

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Named entity recognition on real data: A preliminary investigation for Turkish

Named entity recognition on real data: A preliminary investi...

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international conference on Application of information and Communication Technologies (AICT)

作者： Gökhan Çelikkaya Dilara Torunoğlu Gülsen Eryiğit R&D Department Huawei Technologies Co. Ltd Istanbul 34768 Turkey Istanbul Technical University Institute of Science and Technology Istanbul Turkey Dep. of Computer Engineering Istanbul Technical University Istanbul Turkey

Named Entity Recognition (NER) is a well-studied area in natural language processing (NLP) and the reported results in the literature are generally very high (~>%95) for most of the languages. Today, the focus area of most practical natural language applications (i.e. web mining, sentiment analysis, machine translation) is real natural language data such as web2.0 or speech data. Nevertheless, the NER task is rarely investigated on this type of data which differs severely from formal written text. In this paper, we present 3 new Turkish data sets from different domains (on this focused area; namely from Twitter, a Speech-to-Text Interface and a Hardware Forum) annotated specifically for NER and report our first results on them. We believe, the paper draws light to the difficulty of these new domains for NER and the possible future work.

关键词： Data models Hidden Markov models Twitter Organizations Speech Media Natural language processing

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Scalable Uncertainty Management: 7th international conference, SUM 2013, Washington, DC, USA, September 16-18, 2013. Proceedings 1

引用

丛书名： Lecture Notes in Computer Science 8078

2013年

作者： Anthony Hunter (auth.), Weiru Liu, V. S. Subrahmanian, Jef Wijsen (eds.)

ISBN: (数字)9783642403811

ISBN: (纸本)9783642403804;9783642403811

this book constitutes the refereed proceedings of the 7th international conference on Scalable Uncertainty Management, SUM 2013, held in Washington, DC, USA, in September 2013. the 26 revised full papers and 3 revised short papers were carefully reviewed and selected from 57 submissions. the papers cover topics in all areas of managing and reasoning with substantial and complex kinds of uncertain, incomplete or inconsistent information including applications in decision support systems, machine learning, negotiation technologies, semantic web applications, search engines, ontology systems, information retrieval, natural language processing, information extraction, image recognition, vision systems, data and text mining, and the consideration of issues such as provenance, trust, heterogeneity, and complexity of data and knowledge.

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An application of hidden Markov models in subjectivity analysis

An application of hidden Markov models in subjectivity analy...

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international conference on Application of information and Communication Technologies (AICT)

作者： Samir Rustamov Elshan Mustafayev Mark A. Clements Institute of Cybernetics of Azerbaijan National Academy of Sciences Baku Azerbaijan Georgia Institute of Technology Atlanta USA

Hidden Markov models are a powerful statistical tool and have been used in many areas of speech and natural language processing. In this work, we attempt to detect sentence-level subjectivity by means of hidden Markov model which hasn't been thoroughly investigated for subjectivity analysis. Our feature extraction algorithm calculates a feature vector based on the statistical occurrences of words in a corpus without any linguistic knowledge except tokenization. For this reason, this model can be applied to any language; i.e., there is no lexical, grammatical, syntactical analysis used in the classification process.

关键词： Hidden Markov models Natural language processing Training Classification algorithms Feature extraction Computational modeling Computational linguistics

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