| 书目名称 | Complex Data Analytics with Formal Concept Analysis | | 编辑 | Rokia Missaoui,Léonard Kwuida,Talel Abdessalem | | 视频video | | | 概述 | Covers the state of the art of the research on the intersection of FCA and complex data analysis.An important approach for designing new, accurate, and scalable solutions for big data analytics facili | | 图书封面 |  | | 描述 | FCA is an important formalism that is associated with a variety of research areas such as lattice theory, knowledge representation, data mining, machine learning, and semantic Web. It is successfully exploited in an increasing number of application domains such as software engineering, information retrieval, social network analysis, and bioinformatics. Its mathematical power comes from its concept lattice formalization in which each element in the lattice captures a formal concept while the whole structure represents a conceptual hierarchy that offers browsing, clustering and association rule mining..Complex data analytics refers to advanced methods and tools for mining and analyzing data with complex structures such as XML/Json data, text and image data, multidimensional data, graphs, sequences and streaming data. It also covers visualization mechanisms used to highlight the discovered knowledge..This edited book examines a set of important and relevant research directions in complex data management, and updates the contribution of the FCA community in analyzing complex and large data such as knowledge graphs and interlinked contexts. For example, Formal Concept Analysis and som | | 出版日期 | Book 2022 | | 关键词 | Formal Concept Analysis (FCA); Pattern Visualization; Information Processing; Implication Computation; C | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-93278-7 | | isbn_softcover | 978-3-030-93280-0 | | isbn_ebook | 978-3-030-93278-7 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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发表于 2025-3-21 16:52:08
