標(biāo)題: Titlebook: Complex Data Analytics with Formal Concept Analysis; Rokia Missaoui,Léonard Kwuida,Talel Abdessalem Book 2022 The Editor(s) (if applicable [打印本頁(yè)] 作者: 初生 時(shí)間: 2025-3-21 16:52
書(shū)目名稱Complex Data Analytics with Formal Concept Analysis影響因子(影響力)
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書(shū)目名稱Complex Data Analytics with Formal Concept Analysis讀者反饋
書(shū)目名稱Complex Data Analytics with Formal Concept Analysis讀者反饋學(xué)科排名
作者: CRUMB 時(shí)間: 2025-3-21 22:38 作者: jaunty 時(shí)間: 2025-3-22 01:20
FCA2VEC: Embedding Techniques for Formal Concept Analysis,Superseding ‘latent semantic analysis’ recent approaches like ‘word2vec’ or ‘node2vec’ are well established tools in this realm. In the present paper we add to this line of research by introducing ‘fca2vec’, a family of embedding techniques for formal concept analysis (FCA). Our investigation contri作者: airborne 時(shí)間: 2025-3-22 06:34
Analysis of Complex and Heterogeneous Data Using FCA and Monadic Predicates,simplifies the pattern structure theory proposing to immerse context objects in a dedicated predicate space having the properties of an inference system. This way of managing objects and attributes (monadic predicates) joins the concepts developed in the theory of generalized convex structures, in p作者: 宏偉 時(shí)間: 2025-3-22 11:20 作者: Gratulate 時(shí)間: 2025-3-22 12:58
Computing Dependencies Using FCA,not only in their semantics, but also, in the domains in which they are present: database design, knowledge discovery, data analysis, to name a few. Formal Concept Analysis and Pattern Structures has been used to characterize and compute different kinds of constraints. The fact that this unified fra作者: Gratulate 時(shí)間: 2025-3-22 19:09 作者: CRAMP 時(shí)間: 2025-3-23 01:17 作者: Parley 時(shí)間: 2025-3-23 05:16
Formal Methods in FCA and Big Data,esearch field. The use of FCA in the context of big data provides a basis for better interpretability and explainability of results, usually lacking in other statistical approaches to data analysis; however, scalability is an important issue for FCA logic-based tools and techniques, such as the gene作者: adjacent 時(shí)間: 2025-3-23 06:08
Towards Distributivity in FCA for Phylogenetic Data,of elements such that the infimum of each couple of its elements exists, has an infimum. Since a lattice without its bottom element is obviously a ∨-semilattice, using the FCA formalism, we investigate the following problem: Given a semilattice . obtained from a lattice by deletion of the bottom ele作者: 外形 時(shí)間: 2025-3-23 13:01
Triclustering in Big Data Setting, parallelisation mechanism provided by modern programming languages. OAC-family of triclustering algorithms shows good parallelisation capabilities due to the independent processing of triples of a triadic formal context. We provide time and space complexity of the algorithms and justify their relev作者: mitten 時(shí)間: 2025-3-23 15:21
Analysis of Complex and Heterogeneous Data Using FCA and Monadic Predicates,articular that of half-spaces. We show how this paradigm can be used for boolean, categorized, numerical, character string and sequential data on well-known examples of literature in order to generate lattices whose size is controlled by the user’s choices.作者: 破裂 時(shí)間: 2025-3-23 21:27 作者: MEN 時(shí)間: 2025-3-23 23:49 作者: Allowance 時(shí)間: 2025-3-24 06:24 作者: 不如樂(lè)死去 時(shí)間: 2025-3-24 07:17 作者: growth-factor 時(shí)間: 2025-3-24 13:15 作者: Entreaty 時(shí)間: 2025-3-24 15:56
Book 2022ne 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 th作者: 古文字學(xué) 時(shí)間: 2025-3-24 22:51 作者: 別名 時(shí)間: 2025-3-25 02:38 作者: 煩憂 時(shí)間: 2025-3-25 07:01
FCA2VEC: Embedding Techniques for Formal Concept Analysis,ec approach in low dimension. For both directions the overall constraint of FCA of explainable results is preserved. We evaluate our novel procedures by computing fca2vec on different data sets like, wiki44 (a dense part of the Wikidata knowledge graph), the Mushroom data set and a publication network derived from the FCA community.作者: 喚起 時(shí)間: 2025-3-25 09:40
Dealing with Large Volumes of Complex Relational Data Using RCA,ets with RCA. We also show how pattern extraction combined with the presentation of data in hierarchical structures is appropriate for the analysis of temporal datasets by the domain expert. Finally, we discuss about the possible directions to investigate.作者: 職業(yè)拳擊手 時(shí)間: 2025-3-25 13:51 作者: 使成波狀 時(shí)間: 2025-3-25 17:27 作者: Detonate 時(shí)間: 2025-3-25 22:04 作者: BABY 時(shí)間: 2025-3-26 00:41
Towards Distributivity in FCA for Phylogenetic Data,emilattice, using the FCA formalism, we investigate the following problem: Given a semilattice . obtained from a lattice by deletion of the bottom element, is there a minimum distributive ∨-semilattice .. such that . can be order embedded into ..? We give a negative answer to this question by providing a counter-example.作者: GLUT 時(shí)間: 2025-3-26 06:38
Triclustering in Big Data Setting,e to the independent processing of triples of a triadic formal context. We provide time and space complexity of the algorithms and justify their relevance. We also compare performance gain from using a distributed system and scalability.作者: Intellectual 時(shí)間: 2025-3-26 10:56
Biosynthesis of Plant-Derived Odorants of promising theoretical and practical applications of FCA that could be used to solve the problem of dealing with big data. Furthermore, we propose some directions for future research to solve this problem.作者: overbearing 時(shí)間: 2025-3-26 15:27 作者: Antioxidant 時(shí)間: 2025-3-26 19:37
Rokia Missaoui,Léonard Kwuida,Talel AbdessalemCovers 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作者: 文件夾 時(shí)間: 2025-3-26 20:58
http://image.papertrans.cn/c/image/231415.jpg作者: 文藝 時(shí)間: 2025-3-27 01:53
Helmut Schift Dr.,Anders Kristensen Prof.dies on complex data analytics. The latter refers to the analysis of complex data to discover patterns and learning models from data with a complex structure such as XML or Json data, texts, images, graphs, trees, multidimensional and streaming data. Finally, it presents the contributions inside thi作者: Metamorphosis 時(shí)間: 2025-3-27 07:10 作者: antidote 時(shí)間: 2025-3-27 13:20
Springer Handbook of NanotechnologySuperseding ‘latent semantic analysis’ recent approaches like ‘word2vec’ or ‘node2vec’ are well established tools in this realm. In the present paper we add to this line of research by introducing ‘fca2vec’, a family of embedding techniques for formal concept analysis (FCA). Our investigation contri作者: 高談闊論 時(shí)間: 2025-3-27 16:05 作者: Influx 時(shí)間: 2025-3-27 21:49 作者: 開(kāi)玩笑 時(shí)間: 2025-3-28 01:04
Springer Handbook of Ocean Engineeringnot only in their semantics, but also, in the domains in which they are present: database design, knowledge discovery, data analysis, to name a few. Formal Concept Analysis and Pattern Structures has been used to characterize and compute different kinds of constraints. The fact that this unified fra作者: 檢查 時(shí)間: 2025-3-28 03:59
Biosynthesis of Plant-Derived Odorantsp the emergence of a large amount of data, allowing users to produce, share and exchange various content. Twitter is one of the most popular microblogging sites used by people to find relevant posts that satisfy their information need (e.g., breaking news, popular trends, information about people of作者: osteocytes 時(shí)間: 2025-3-28 07:17
Anne Plotto,Jinhe Bai,Elisabeth Baldwin of large data sets poses four fundamental challenges: the time required to enumerate the vertices, arcs and labels of the lattice digraph; the difficulty of responsive presentation of, and meaningful user interaction with, a large digraph; the time required to enumerate (a basis for) all valid impl作者: Melanocytes 時(shí)間: 2025-3-28 14:29
Biosynthesis of Plant-Derived Odorantsesearch field. The use of FCA in the context of big data provides a basis for better interpretability and explainability of results, usually lacking in other statistical approaches to data analysis; however, scalability is an important issue for FCA logic-based tools and techniques, such as the gene作者: 暫時(shí)中止 時(shí)間: 2025-3-28 15:31
Odors in Paper and Cardboard Packagingof elements such that the infimum of each couple of its elements exists, has an infimum. Since a lattice without its bottom element is obviously a ∨-semilattice, using the FCA formalism, we investigate the following problem: Given a semilattice . obtained from a lattice by deletion of the bottom ele作者: intelligible 時(shí)間: 2025-3-28 21:48
Jane M. Simmons,George N. Rouskas parallelisation mechanism provided by modern programming languages. OAC-family of triclustering algorithms shows good parallelisation capabilities due to the independent processing of triples of a triadic formal context. We provide time and space complexity of the algorithms and justify their relev作者: Antigen 時(shí)間: 2025-3-29 02:53
Helmut Schift Dr.,Anders Kristensen Prof.dies on complex data analytics. The latter refers to the analysis of complex data to discover patterns and learning models from data with a complex structure such as XML or Json data, texts, images, graphs, trees, multidimensional and streaming data. Finally, it presents the contributions inside this volume.作者: 小卒 時(shí)間: 2025-3-29 04:47 作者: browbeat 時(shí)間: 2025-3-29 08:44
978-3-030-93280-0The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: GULP 時(shí)間: 2025-3-29 15:03 作者: Hemodialysis 時(shí)間: 2025-3-29 19:23
