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Complex data analytics with formal concept analysis / Rokia Missaoui, Léonard Kwuida, Talel Abdessalem, editors.

Missaoui, R.; Kwuida, Leonard.; Abdessalem, Talel.
2022
QA76.9.D343
Available Online
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Title
Complex data analytics with formal concept analysis / Rokia Missaoui, Léonard Kwuida, Talel Abdessalem, editors.
ISBN
9783030932787 (electronic bk.)
3030932788 (electronic bk.)
303093277X
9783030932770
DOI
https://doi.org/10.1007/978-3-030-93278-7
Published
Cham : Springer, 2022.
Language
English
Description
1 online resource (277 pages)
Item Number
10.1007/978-3-030-93278-7 doi
Call Number
QA76.9.D343
Dewey Decimal Classification
006.3/12
Summary
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 some of its extensions are exploited, revisited and coupled with recent processing parallel and distributed paradigms to maximize the benefits in analyzing large data.
Bibliography, etc. Note
Includes bibliographical references and index.
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Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed July 14, 2022).
Added Author
Missaoui, R.
Kwuida, Leonard.
Abdessalem, Talel.
Available in Other Form
Complex Data Analytics with Formal Concept Analysis
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Chapter. 1
Formal Concept Analysis and Extensions for Complex Data Analytics
Chapter. 2
Conceptual Navigation in Large Knowledge Graphs
Chapter. 3
FCA2VEC: Embedding Techniques for Formal Concept Analysis
Chapter. 4
Analysis of Complex and Heterogeneous Data using FCA and Monadic Predicates
Chapter. 5
Dealing with Large Volumes of Complex Relational Data using RCA
Chapter. 6
Computing Dependencies using FCA
Chapter. 7
Leveraging Closed Patterns and Formal Concept Analysis for Enhanced Microblogs Retrieval
Chapter. 8
Scalable Visual Analytics in FCA
Chapter. 9
Formal methods in FCA and Big Data
Chapter. 10
Towards Distributivity in FCA for Phylogenetic Data
Chapter. 11
Triclustering in Big Data Setting.

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