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- item-2 hasContent keita-tsuji.
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- item-3 hasContent shigeo-sugimoto.
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- 405 creator jun-okamoto.
- 405 creator kiyoko-uchiyama.
- 405 creator shun-ishizaki.
- 405 type InProceedings.
- 405 label "A Contextual Dynamic Network Model for WSD Using Associative Concept Dictionary".
- 405 sameAs 405.
- 405 abstract "Many of the Japanese ideographs (Chinese characters) have a few meanings. Such ambiguities should be identified by using their contextual information. For example, we have an ideograph which has two pronunciations, /hitai/ and /gaku/, the former means a forehead of the human body and the latter has two meanings, an amount of money and a picture frame. Conventional methods for such a disambiguation problem have been using statistical methods with co-occurrence of words in their context. In this research, Contextual Dynamic Network Model is developed using the Associative Concept Dictionary which includes semantic relations among concepts/words and the relations can be represented with quantitative distances. In this model, an interactive activation method is used to identify a word s meaning on the Contextual Semantic Network where the activation on the network is calculated using the distances. The proposed method constructs dynamically the Contextual Semantic Network according to the input words sequentially that appear in the sentence including an ambiguous word.".
- 405 hasAuthorList authorList.
- 405 hasTopic Linguistics.
- 405 isPartOf proceedings.
- 405 keyword "Language modelling".
- 405 keyword "Ontologies".
- 405 keyword "Word Sense Disambiguation".
- 405 title "A Contextual Dynamic Network Model for WSD Using Associative Concept Dictionary".
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- item-1 hasContent jun-okamoto.
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- 407 creator abdel-rahim-madany.
- 407 creator hossam-ibrahim.
- 407 creator kareem-darwish.
- 407 type InProceedings.
- 407 label "Automatic Extraction of Textual Elements from News Web Pages".
- 407 sameAs 407.
- 407 abstract "In this paper we present an algorithm for automatic extraction of textual elements, namely titles and full text, associated with news stories in news web pages. We propose a supervised machine learning classification technique based on the use of a Support Vector Machine (SVM) classifier to extract the desired textual elements. The technique uses internal structural features of a webpage without relying on the Document Object Model to which many content authors fail to adhere. The classifier uses a set of features which rely on the length of text, the percentage of hypertext, etc. The resulting classifier is nearly perfect on previously unseen news pages from different sites. The proposed technique is successfully employed in Alzoa.com, which is the largest Arabic news aggregator on the web.".
- 407 hasAuthorList authorList.
- 407 hasTopic Linguistics.
- 407 isPartOf proceedings.
- 407 keyword "Corpus (creation, annotation, etc.)".
- 407 keyword "LR web services".
- 407 keyword "Text mining".
- 407 title "Automatic Extraction of Textual Elements from News Web Pages".
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- item-1 hasContent hossam-ibrahim.
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- item-2 hasContent kareem-darwish.
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- 409 creator aaron-johnson.
- 409 creator c-ray-graham.
- 409 creator casey-kennington.
- 409 creator deryle-lonsdale.
- 409 creator jeremiah-mcghee.
- 409 type InProceedings.
- 409 label "Elicited Imitation as an Oral Proficiency Measure with ASR Scoring".
- 409 sameAs 409.
- 409 abstract "This paper discusses development and evaluation of a practical, valid and reliable instrument for evaluating the spoken language abilities of second-language (L2) learners of English. First we sketch the theory and history behind elicited imitation (EI) tests and the renewed interest in them. Then we present how we developed a new test based on various language resources, and administered it to a few hundred students of varying levels. The students were also scored using standard evaluation techniques, and the EI results were compared to more traditionally derived scores. We also sketch how we developed a new integrated tool that allows the session recordings of the EI data to be analyzed with a widely-used automatic speech recognition (ASR) engine. We discuss the promising results of the ASR engine s processing of these files and how they correlated with human scoring of the same items. We indicate how the integrated tool will be used in the future. Further development plans and prospects for follow-on work round out the discussion.".
- 409 hasAuthorList authorList.
- 409 hasTopic Linguistics.
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- 409 keyword "Evaluation methodologies".
- 409 keyword "Speech recognition and understanding".
- 409 keyword "Tools, systems, applications".
- 409 title "Elicited Imitation as an Oral Proficiency Measure with ASR Scoring".
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- item-1 hasContent c-ray-graham.
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