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Titlebook: Knowledge Science, Engineering and Management; 9th International Co Franz Lehner,Nora Fteimi Conference proceedings 2016 Springer Internati

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書目名稱Knowledge Science, Engineering and Management
副標(biāo)題9th International Co
編輯Franz Lehner,Nora Fteimi
視頻videohttp://file.papertrans.cn/545/544040/544040.mp4
概述Includes supplementary material:
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Knowledge Science, Engineering and Management; 9th International Co Franz Lehner,Nora Fteimi Conference proceedings 2016 Springer Internati
描述.This book constitutes the refereed proceedings of the 9th International Conference on Knowledge Science, Engineering and Management, KSEM 2016, held in Passau, Germany, in October 2016. ..The 49 revised full papers presented together with 2 keynotes were carefully selected and reviewed from 116 submissions. The papers are organized in topical sections on Clustering and Classification; Text Mining and Lexical Analysis; Content and Document Analysis; Enterprise Knowledge; Formal Semantics and Fuzzy Logic; Knowledge Engineering; Knowledge Enrichment and Visualization; Knowledge Management; Knowledge Retrieval; Knowledge Systems and Security; Neural Networks and Artificial Intelligence; Ontologies; and Recommendation Algorithms and Systems.?.
出版日期Conference proceedings 2016
關(guān)鍵詞enterprise ontologies; formal semantics; knowledge representation and reasoning; natural language proce
版次1
doihttps://doi.org/10.1007/978-3-319-47650-6
isbn_softcover978-3-319-47649-0
isbn_ebook978-3-319-47650-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing AG 2016
The information of publication is updating

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Increasing Topic Coherence by Aggregating Topic Models to calculate the coherence of topics in the base models against those of the aggregated model. The results presented in this paper show that the aggregated model outperforms standard topic models at a statistically significant level in terms of topic coherence when evaluated against an external corpus.
地板
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Analyzing Topic-Sentiment and Topic Evolution over Time from Social Mediabution over time and a Dirichlet distribution with respect to the sentiment. We evaluate our method on the real-world news dataset. The experimental results show that we have achieved high correlation between the topic and sentiment, better interpretable topic evolution, and higher document sentiment classification result and perplexity.
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An Unsupervised Framework Towards Sci-Tech Compound Entity Recognitiondicative words used in segment validating is reduced to the classical minimum set cover problem. Experimental results on classifying real-world science-technology entities show that SCSegVal achieves a sharp increase comparing with the classical supervised HMM-based approach.
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When IT Leveraging Competence Meets Uncertainty and Complexity with Social Capital in New Product Debut the complexity has no moderating effect on this link. Our findings reveal why the NPD teams may have difficulty achieving high levels of performance and why these teams may vary in their ability to create the value from their COOR and ACAP.
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Adoption Factors for Crowdsourcing Based Medical Information Platformse it is increased by crowdsourcing features. Additionally, external motivation yields important influence factors. The revealed interrelations are discussed and should be accounted for in future research and implementations.
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0302-9743 ngineering and Management, KSEM 2016, held in Passau, Germany, in October 2016. ..The 49 revised full papers presented together with 2 keynotes were carefully selected and reviewed from 116 submissions. The papers are organized in topical sections on Clustering and Classification; Text Mining and Le
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