Get Bridging Between Information Retrieval and Databases: PDF

By Nicola Ferro

ISBN-10: 3642547974

ISBN-13: 9783642547973

ISBN-10: 3642547982

ISBN-13: 9783642547980

The examine domain names of data retrieval and databases have normally followed diversified techniques to details administration. even if, lately, there was an expanding cross-fertilization one of the fields and now many study demanding situations are transversal to them. With this in brain, a wintry weather college used to be geared up in Bressanone, Italy, in February 2013, in the context of the EU-funded learn venture PROMISE (Participative learn Laboratory for Multimedia and Multilingual details structures Evaluation). PROMISE aimed toward advancing the experimental overview of advanced multimedia and multilingual details platforms to be able to aid members, advertisement entities and groups, who layout, enhance, hire and enhance such advanced platforms. the general target of PROMISE was once to bring a unified setting gathering facts, wisdom, instruments and methodologies and to assist the consumer neighborhood fascinated with experimental evaluate. This booklet constitutes the result of the PROMISE wintry weather university 2013 and comprises nine invited lectures from the study domain names of data retrieval and databases plus brief papers of the easiest scholar poster awards. a wide number of issues are coated, together with databases, info retrieval, experimental assessment, metrics and records, semantic seek, key-phrase seek in databases, semi-structured seek, evaluate either in info retrieval and databases, crowdsourcing and social media.

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Extra info for Bridging Between Information Retrieval and Databases: PROMISE Winter School 2013, Bressanone, Italy, February 4-8, 2013. Revised Tutorial Lectures

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Overview of the eighth text retrieval conference (trec8). In: NIST Special Publication 500-246: The Eighth Text REtrieval Conference (TREC 8), pp. 1–24 (2000) 29. , et al. ): CLEF 2008. LNCS, vol. 5706. Springer, Heidelberg (2009) 30. : Characterizing microblogs with topic models. In: ICWSM (2010) 31. : Structural analysis of chat messages for topic detection. Online Information Review, 496–516 (2006) 32. : Combining topic models and social networks for chat data mining. In: WI 2004: Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence, pp.

P 3r g n sin no n o rb rs Ve pe rm fo rb Ve b e iv ct je Ad e cl ti Ar l) n ra r tion o c ou lu N (p ion jun oun it n n os co pro ep b. ) (:) m m co n d rio lo co pe (c) high frequency punctuation (d) interjections, symbols and low frequency punctuation Fig. 7. POS analysis one grammatical category: the framework GATE 22 and its component ANNIE23 [35, 36] dedicated to this kind of analysis, called Part-Of-Speech (POS) analysis. In Figure 7 we report the results of the POS analysis of the full text on 30% of the documents in the collection, selected at random (since we did not find significant variation in the distributions with an higher subset).

Alternatively, Google refers to such semantics as knowledge graphs and to semantic search as “searching for things, not strings” [6]. Semantic search requires some natural language processing techniques for understanding word meaning. Since some of the most frequently used searches are for persons, locations, organisations, and other named entities [7], one of the most widely used techniques for interpreting this meaning are named entity recognition [8] and semantic annotation [9]. e. ) enables semantic search queries such as “LOC earthquake” which would return all documents mentioning a location and the word earthquake.

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Bridging Between Information Retrieval and Databases: PROMISE Winter School 2013, Bressanone, Italy, February 4-8, 2013. Revised Tutorial Lectures by Nicola Ferro

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