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By Lukas Michelbacher, Qi Han, Hinrich Schütze (auth.), Alexander Gelbukh (eds.)

This two-volume set, including LNCS 7816 and LNCS 7817, constitutes the completely refereed court cases of the thirteenth foreign convention on desktop Linguistics and clever Processing, CICLING 2013, hung on Samos, Greece, in March 2013. the entire of ninety one contributions offered used to be conscientiously reviewed and chosen for inclusion within the complaints. The papers are geared up in topical sections named: common strategies; lexical assets; morphology and tokenization; syntax and named entity attractiveness; notice feel disambiguation and coreference answer; semantics and discourse; sentiment, polarity, subjectivity, and opinion; computing device translation and multilingualism; textual content mining, info extraction, and knowledge retrieval; textual content summarization; stylometry and textual content simplification; and applications.

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Extra resources for Computational Linguistics and Intelligent Text Processing: 14th International Conference, CICLing 2013, Samos, Greece, March 24-30, 2013, Proceedings, Part I

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C) One would expect in-domain performance to be better than cross-domain performance and this is the case for Den . However, for two of the domains, Dde and Dph , feature adaptation rivals in-domain performance. For Dph and Dde the in-domain systems do not bring significant improvements over feature adaptation. This is particularly interesting in the cross-topic setting Den → Dph , where we apply the model learned on a more general domain (web corpus) to a specialized domain (physics) without a performance drop.

An overview of BabelNet is given in Figure 2. The excerpt highlights that WordNet and Wikipedia can overlap both in terms of concepts and relations: accordingly, in order to provide a unified resource, we merge the intersection of these 28 R. Navigli two knowledge sources. Next, to enable multilinguality, we collect the lexical realizations of the available concepts in different languages. Finally, we connect the multilingual Babel synsets by establishing semantic relations between them. Thus, our methodology consists of three main steps: 1.

Org. 1, overviewed the new interface for search and graph exploration, and surveyed the Java programmatic API. This resource has already proven useful in tasks such as multilingual Word Sense Disambiguation [13] and semantic relatedness [12], but many horizons are still to be explored. Acknowledgments. The author gratefully acknowledges the support of the ERC Starting Grant MultiJEDI No. 259234. Thanks go to Daniele Vannella for his help on calculating statistics. References 1. : Dbpedia - a crystallization point for the web of data.

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