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Titlebook: Ontologies and Concepts in Mind and Machine; 25th International C Mehwish Alam,Tanya Braun,Bruno Yun Conference proceedings 2020 Springer N

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書目名稱Ontologies and Concepts in Mind and Machine
副標題25th International C
編輯Mehwish Alam,Tanya Braun,Bruno Yun
視頻videohttp://file.papertrans.cn/702/701698/701698.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Ontologies and Concepts in Mind and Machine; 25th International C Mehwish Alam,Tanya Braun,Bruno Yun Conference proceedings 2020 Springer N
描述.This book constitutes the proceedings of the 25th International Conference on Conceptual Structures, ICCS 2020, held in Bolzano, Italy, in September 2020.*..The 10 full papers, 5 short papers and 1 poster paper presented were carefully reviewed and selected from 24 submissions. The proceedings also include two keynotes and two tutorials. The papers focus on the representation of and reasoning with conceptual structures in a variety of contexts. The topics of this year‘s conference range from formal concept analysis to decision making, from machine learning to natural language processing...*.The conference was held virtually due to the COVID-19 pandemic..
出版日期Conference proceedings 2020
關(guān)鍵詞artificial intelligence; computer programming; computer systems; concept lattices; data mining; databases
版次1
doihttps://doi.org/10.1007/978-3-030-57855-8
isbn_softcover978-3-030-57854-1
isbn_ebook978-3-030-57855-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

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An Incremental Algorithm for Computing All Repairs in Inconsistent Knowledge Bases while certain applications need the generation of all repairs. In this paper, we show that the problem of all repair computation is not trivial in practice. To account for a scalable solution, we provide an incremental approach for the computation of all repairs when the conflicts have a cardinalit
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Preventing Overlaps in Agglomerative Hierarchical Conceptual Clusteringumed that the result is a tree-like structure with no overlapping clusters, i.e., where clusters are either disjoint or nested. In Hierarchical Conceptual Clustering (HCC), each cluster is provided with a conceptual description which belongs to a predefined set called the .. Depending on the applica
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Pruning in Map-Reduce Style CbO Algorithms (shortly, CbO-based algorithms). State-of-the-art CbO-based algorithms, e.g. FCbO, In-Close4, and In-Close5, employ several techniques, which we call pruning, to avoid some unnecessary computations. However, the number of the formal concepts can be exponential w.r.t. dimension of the input data. Th
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Characterizing Movie Genres Using Formal Concept Analysists and genres are attribute. The context is then used to find formal concepts organized in a concept lattice. This conceptual structure is useful to measure semantic genre-based similarity of movies, which is important for content-based recommender systems.
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