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Titlebook: Natural Language Processing and Information Systems; 14th International C Helmut Horacek,Elisabeth Métais,Magdalena Wolska Conference proce

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發(fā)表于 2025-3-21 16:23:46 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Natural Language Processing and Information Systems
副標(biāo)題14th International C
編輯Helmut Horacek,Elisabeth Métais,Magdalena Wolska
視頻videohttp://file.papertrans.cn/662/661832/661832.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Natural Language Processing and Information Systems; 14th International C Helmut Horacek,Elisabeth Métais,Magdalena Wolska Conference proce
描述This volume contains the papers presented at NLDB 2009, the 14th Inter- tional Conference on Applications of Natural Language to Information Systems held June 24–26, 2009, at the University of the Saarland and the German - search Center for Arti?cial Intelligence in Saarbruc ¨ ken, Germany. In addition to reviewed submissions, the program also included contributions to the doctoral symposiumheldduring NLDB2009aswellastwoinvitedtalks.Thesetalksc- ered some of the currently hot topics in the use of natural languagefor accessing information systems. Wereceived51submissionsasregularpapersforthemainconference,2extra submissions as posters, and 3 short papers for the doctoral symposium. Each paper for the main conference was assigned four reviewers, taking into account preferences expressed by the ProgramCommittee members as much as possible. Within the review deadline, we received at least three reviews for almost all submissions. After the review deadline, the Conference Organizing Committee members and the Program Committee Chair acted as meta-reviewers. This task included studying the reviews and the papers, speci?cally those whose assessment made them borderline cases, and discussin
出版日期Conference proceedings 2010
關(guān)鍵詞Processing; S-Lang; SQL; Text Mining; algorithms; classification; cognition; knowledge; knowledge base; machi
版次1
doihttps://doi.org/10.1007/978-3-642-12550-8
isbn_softcover978-3-642-12549-2
isbn_ebook978-3-642-12550-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2010
The information of publication is updating

書目名稱Natural Language Processing and Information Systems影響因子(影響力)




書目名稱Natural Language Processing and Information Systems影響因子(影響力)學(xué)科排名




書目名稱Natural Language Processing and Information Systems網(wǎng)絡(luò)公開度




書目名稱Natural Language Processing and Information Systems網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Natural Language Processing and Information Systems被引頻次




書目名稱Natural Language Processing and Information Systems被引頻次學(xué)科排名




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Analysis and Improvement of Minimally Supervised Machine Learning for Relation Extractionethod is based on a bootstrapping approach in which the bootstrapping is triggered by semantic seeds. The starting point of our analysis is the pattern-learning graph which is a subgraph of the bipartite graph representing all connections between linguistic patterns and relation instances exhibited
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Using Evidences Based on Natural Language to Drive the Process of Fusing Multimodal Sourcesals are based on two widely used fusion strategies in the VIR area, the multimodal blind relevance feedback and the multimodal re-ranking strategy. Unlike the existent techniques, our alternative proposals are guided by the evidence found in the natural language annotations related to the images. Th
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An Experimental Comparison of Explicit Semantic Analysis Implementations for Cross-Language Retrievan texts) and has thus a natural application in information retrieval, showing the potential to alleviate the vocabulary mismatch problem inherent in standard Bag-of-Word models. The ESA model has been also recently extended to cross-lingual retrieval settings, which can be considered as an extreme c
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Requirements Analysis: Concept Extraction and Translation of Textual Specifications to Executable Mo documents are often inconsistent and incomplete. In industrial requirements documents, natural language is the main presentation means. This results in the fact that the requirements documents are imprecise, incomplete, and inconsistent. A viable way to detect inconsistencies and omissions in docum
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