By Manuela Angioni, Emanuela De Vita (auth.), Vincenzo Pallotta, Alessandro Soro, Eloisa Vargiu (eds.)
This quantity comprises revised and prolonged models of papers provided on the 4th version of the foreign workshop on disbursed and Agent-based Retrieval Toos (DART'10) held in June 2010, along with the Symposium on Human Language know-how for the knowledge Society, in Geneva, Swizerland. Practitioners and researchers engaged on pervasive and clever entry to net providers and disbursed info retrieval met to percentage their effects and insights in interesting and hard issues akin to: (i) social media and collaboration, (ii) new demanding situations in seek know-how, (iii) sentiment research and opinion mining, (iv) disbursed info retrieval, (v) pervasive intelligence. each bankruptcy, prior to discussing intensive the categorical subject, offers a accomplished evaluate of similar paintings and cutting-edge, within the desire of this quantity to be of use within the future years, to either researchers and students.
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Additional resources for Advances in Distributed Agent-Based Retrieval Tools
RefGen identifies reference chains and it uses genre specific properties of reference chains and (Ariel 1990)’s accessibility theory. RefGen checks several strong and weak constraints (lexical, morphosyntactic and semantic filters) to automatically identify coreference relations between referential expressions. We present the first results obtained by RefGen from a public reports corpus. 1 Introduction We present a project aiming at automatic topic detection, by combining statistical methods and linguistic methods.
These markers point out the entity frequently referred in a paragraph. First, we identify the reference chains from each discourse segment. Then, we propose local candidate topics for each document segment, selecting them from the first elements of the reference chains. The first mention refers to a new discourse entity, so it represents a potential local topic. While our goal is to select a global topic associated to the document, we Laurence Longo · Amalia Todiraşcu LiLPa laboratory, University of Strasbourg, 67000 Strasbourg, France V.
Longo and A. Todiraşcu “colonel”/‘colonel’) for two reasons. First, because function names may be associated with a person name (relation between the person name and its function), as “Dominique Muller – président du conseil” / ’Dominique Muller – chairman of the board’ to reinforce the link between entities. Second, because function names are good proofs to categorize person names and organisation names (internal and external evidences (McDonald 1996)). In this sense, our named entity extractor first defines the boundaries of the named entity (by adding the attribute ‘Ner=”NER”) and then it assigns the type of the entity (“Org”, “Pers”, “Func”).
Advances in Distributed Agent-Based Retrieval Tools by Manuela Angioni, Emanuela De Vita (auth.), Vincenzo Pallotta, Alessandro Soro, Eloisa Vargiu (eds.)