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- item-2 hasContent raquel-mochales-palau.
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- 651 creator piotr-banski.
- 651 creator radoslaw-moszczynski.
- 651 type InProceedings.
- 651 label "Enhancing an English-Polish Electronic Dictionary for Multiword Expression Research".
- 651 sameAs 651.
- 651 abstract "This paper describes a project aimed at converting a legacy representation of English idioms into an XML-based format. The project is set in the context of a large electronic English-Polish dictionary which contains several hundred formalized idiom descriptions and which has been released under the terms of a free license. In short, the project consists of three phases: cleaning up the dictionary markup, extracting the legacy idiom representations, and converting them into TEI P5 XML constrained by a RelaxNG grammar created for this purpose and constituting a module that can be included as part of the TEI P5 schema. The paper contains general descriptions of the individual phases and several examples of XML-encoded idioms. It also suggests some directions for further research, which include abstracting the XML-ized idiom representations into general syntactic patterns and using the representations to automatically identify idioms in tagged corpora.".
- 651 hasAuthorList authorList.
- 651 hasTopic Linguistics.
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- 651 keyword "LR Infrastructures and Architectures".
- 651 keyword "Lexicon, lexical database".
- 651 keyword "MultiWord Expressions & Collocations".
- 651 title "Enhancing an English-Polish Electronic Dictionary for Multiword Expression Research".
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- 652 creator claire-waast-richard.
- 652 creator frederik-cailliau.
- 652 creator gilles-adda.
- 652 creator lori-lamel.
- 652 creator martine-garnier-rizet.
- 652 creator stephan-vanni.
- 652 creator sylvie-guillemin-lanne.
- 652 type InProceedings.
- 652 label "CallSurf: Automatic Transcription, Indexing and Structuration of Call Center Conversational Speech for Knowledge Extraction and Query by Content".
- 652 sameAs 652.
- 652 abstract "Being the client s first interface, call centres worldwide contain a huge amount of information of all kind under the form of conversational speech. If accessible, this information can be used to detect eg. major events and organizational flaws, improve customer relations and marketing strategies. An efficient way to exploit the unstructured data of telephone calls is data-mining, but current techniques apply on text only. The CallSurf project gathers a number of academic and industrial partners covering the complete platform, from automatic transcription to information retrieval and data mining. This paper concentrates on the speech recognition module as it discusses the collection, the manual transcription of the training corpus and the techniques used to build the language model. The NLP techniques used to pre-process the transcribed corpus for data mining are POS tagging, lemmatization, noun group and named entity recognition. Some of them have been especially adapted to the conversational speech characteristics. POS tagging and preliminary data mining results obtained on the manually transcribed corpus are briefly discussed.".
- 652 hasAuthorList authorList.
- 652 hasTopic Linguistics.
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- 652 keyword "Speech recognition and understanding".
- 652 keyword "Speech resource/database".
- 652 keyword "Text mining".
- 652 title "CallSurf: Automatic Transcription, Indexing and Structuration of Call Center Conversational Speech for Knowledge Extraction and Query by Content".
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- 654 creator mehrnoush-shamsfard.
- 654 type InProceedings.
- 654 label "Towards Semi Automatic Construction of a Lexical Ontology for Persian".
- 654 sameAs 654.
- 654 abstract "Lexical ontologies and semantic lexicons are important resources in natural language processing. They are used in various tasks and applications, especially where semantic processing is evolved such as question answering, machine translation, text understanding, information retrieval and extraction, content management, text summarization, knowledge acquisition and semantic search engines. Although there are a number of semantic lexicons for English and some other languages, Persian lacks such a complete resource to be used in NLP works. In this paper we introduce an ongoing project on developing a lexical ontology for Persian called FarsNet. We exploited a hybrid semi-automatic approach to acquire lexical and conceptual knowledge from resources such as WordNet, bilingual dictionaries, mono-lingual corpora and morpho-syntactic and semantic templates. FarsNet is an ontology whose elements are lexicalized in Persian. It provides links between various types of words (cross POS relations) and also between words and their corresponding concepts in other ontologies (cross ontologies relations). FarsNet aggregates the power of WordNet on nouns, the power of FrameNet on verbs and the wide range of conceptual relations from ontology community.".
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