{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":1,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":19,"n_cols":5,"rows_kept":19,"cut":false,"hidden":false,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[3,2,3,3],[4,2,4,3],[5,2,5,3],[6,2,6,3],[7,2,7,3],[8,2,8,3],[9,2,9,3],[12,2,12,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNISA996464493303316"]
[null,null,"Titolo",null,"Formal concept analysis : 16th international conference, ICFCA 2021, Strasbourg, France, June 29 - July 2, 2021 : proceedings / / Agnès Braud [and three others], editors"]
[null,null,"Pubbl/distr/stampa",null,"Cham, Switzerland : , : Springer, , 2021"]
[null,null,"ISBN",null,"3-030-77867-3"]
[null,null,"Descrizione fisica",null,"1 online resource (299 pages)"]
[null,null,"Collana",null,"Lecture notes in computer science ; ; 12733"]
[null,null,"Disciplina",null,"004.0151"]
[null,null,"Soggetti",null,"Formal methods (Computer science)"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Includes author index."]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Abstracts of Invited Talks -- What do the Sources Say? Exploring Heterogeneous Journalistic Data as a Graph -- Ontologies for On-Demand Design of Data-Centric Systems -- Towards Human-Guided Rule Learning -- Sustainable AI - What Does It Take for Continued Success in Deployed Applications? -- Contents -- Theory -- Representing Partition Lattices Through FCA -- 1 Introduction -- 2 Preliminaries -- 2.1 Lattices and Partitions -- 2.2 Notions of Formal Concept Analysis -- 3 Relation Between the Lattices Ln and Ln+1 -- 4 Standard Context of Ln -- References -- Fixed-Point Semantics for Barebone Relational Concept Analysis -- 1 Motivation -- 2 Preliminaries and Related Work -- 2.1 Formal Concept Analysis -- 2.2 Extending FCA -- 2.3 Relational Concept Analysis -- 2.4 RCA0 -- 3 RCA May Accept Different Concept Lattice Families: Illustration -- 4 Semantics and Properties: A Context Approach -- 4.1 The Lattice K of RCA0 Contexts -- 4.2 The Context Expansion Function F -- 4.3 Fixed Points of F -- 4.4 The Well-Grounded Semantics of RCA is the Least Fixed-Point Semantics -- 4.5 Computing the Greatest Fixed Point -- 5 Self-supported Fixed Points -- 5.1 The Lattice L of RCA0 Lattices and the Lattice Expansion Function E -- 5.2 Self-supported Lattices -- 6 Discussion -- 7 Conclusions -- References -- Boolean Substructures in Formal Concept Analysis -- 1 Introduction -- 2 Recap on FCA and Notations -- 2.1 Foundations -- 2.2 Relating Substructures in FCA -- 3 Related Work -- 4 Boolean Subcontexts and Sublattices -- 5 Closed-Subcontexts -- 6 Connecting Boolean Suborders and Boolean Subcontexts -- 6.1 Embeddings of Boolean Substructures -- 6.2 Subconcepts Associated to Suborders -- 7 Interplay of Both "]
[{"$nulls":4},"Approaches -- 8 Conclusion -- References -- Rules -- Enumerating Maximal Consistent Closed Sets in Closure Systems."]
[{"$nulls":4},"1 Introduction -- 2 Preliminaries -- 3 Closure Systems Given by Implicational Bases -- 4 Minimal Generators with Bounded Size -- 5 Biatomic Atomistic Closure Systems -- 6 Conclusions -- References -- A New Kind of Implication to Reason with Unknown Information -- 1 Introduction -- 2 Preliminaries -- 2.1 FCA Preliminaries -- 2.2 Attribute Implications -- 3 An Algebraic Framework for Unknown Information -- 3.1 The -semilattice of 3-sets -- 3.2 The Lattices of 4-sets and -sets -- 4 Extending the Concept of Lattice -- 5 Reasoning with Weak Implications -- 6 Conclusion and Further Work -- References -- Pruning Techniques in LinCbO for Computation of the Duquenne-Guigues Basis -- 1 Introduction -- 2 Preliminaries -- 2.1 Formal Concept Analysis, Theories, Models, and Bases -- 2.2 Duquenne-Guigues Basis -- 2.3 LinCbO -- 3 Pruning in Pseudointent Computation -- 4 How LinCbO Utilizes the Pruning -- 5 Experimental Evaluation -- 6 Our Observations -- 7 Conclusion -- References -- Approximate Computation of Exact Association Rules -- 1 Introduction -- 2 Main Definitions -- 3 Probably Approximately Correct Computation of Implications -- 4 Computing Frequency-Aware Approximations -- 5 Experimental Evaluation -- 5.1 Quality Factor -- 5.2 Testbed -- 5.3 Data Sets -- 5.4 Experiments -- 6 Conclusion -- References -- Methods and Applications -- An Incremental Recomputation of From-Below Boolean Matrix Factorization -- 1 Introduction -- 2 Problem Description -- 2.1 Non-incremental From-Below BMF -- 2.2 Incremental From-Below BMF -- 3 Incremental Algorithm -- 3.1 Adding of New Entries -- 3.2 Removing of Existing Entries -- 3.3 Time Complexity -- 4 Experimental Evaluation -- 4.1 Datasets -- 4.2 Adding of New Entries -- 4.3 Removing of Existing Entries -- 4.4 Running Times -- 5 Conclusions -- References -- Clustering and Identification of Core Implications -- 1 Introduction."]
[{"$nulls":4},"2 Previous Works on FCA and Clustering -- 3 Background and the fcaR package -- 4 Proposed Research Line -- 5 Experimental Results -- 6 Conclusions -- References -- Extracting Relations in Texts with Concepts of Neighbours -- 1 Introduction -- 2 Preliminaries -- 3 Modeling Sentences as Graphs -- 3.1 NLP Treatments -- 3.2 Sentences as an RDF Graph -- 3.3 Type Hierarchies -- 4 Relation Extraction with Concepts of Neighbours -- 4.1 Concepts of Neighbours for Relation Extraction in Texts -- 4.2 Scoring Methods -- 5 Experiments -- 5.1 Dataset and Baseline -- 5.2 Experimental Settings -- 5.3 Quantitative Results -- 5.4 Qualitative Results -- 6 Conclusion -- References -- Exploration and Visualisation -- Triadic Exploration and Exploration with Multiple Experts -- 1 Introduction -- 2 Dyadic and Triadic Formal Contexts -- 2.1 Formal Concept Analysis -- 2.2 Triadic Concept Analysis -- 2.3 Attribute Implications -- 2.4 Attribute Exploration -- 3 Triadic Exploration -- 3.1 Conditional Attribute Implications -- 3.2 Triadic Exploration -- 3.3 An Example for Triadic Exploration -- 4 Application for Exploration with Multiple Experts -- 5 Conclusion and Outlook -- References -- Towards Interactive Transition from AOC Poset to Concept Lattice -- 1 Introduction -- 1.1 Formal Concept Analysis and Scalability -- 1.2 AOC Poset -- 1.3 Morphing AOC Poset into Concept Lattice -- 1.4 Generating only Abstract Concepts -- 1.5 Organisation -- 2 Context Ablation -- 2.1 Preliminaries -- 2.2 Strategy -- 2.3 Elimination of Bigraph Elements -- 2.4 Iterative Edge Elimination -- 3 Formal Concept Analysis of Ablated Context -- 3.1 Finding Valid Abstract Concepts -- 3.2 Dividing and Conquering -- 3.3 Anticipating and Localising Change in the AOC Poset -- 4 Discussion and Summary -- References -- Visualization of Statistical Information in Concept "]
[{"$nulls":4},"Lattice Diagrams."]
[{"$nulls":4},"Force-Directed Layout of Order Diagrams Using Dimensional Reduction -- 1 Introduction -- 2 Related Work -- 3 Fundamentals and Basics -- 3.1 Mathematical Notations and Definitions -- 3.2 Force-Directed Graph Drawing -- 4 The ReDraw Algorithm -- 4.1 Node Step -- 4.2 Line Step -- 4.3 Dimension Reduction -- 5 Evaluation -- 5.1 Run-Time Complexity -- 5.2 Tested Datasets -- 5.3 Recommended Parametrizations -- 5.4 Empirical Evaluation -- 5.5 User Evaluation -- 6 Conclusion and Outlook -- References -- Short Papers -- Sandwich: An Algorithm for Discovering Relevant Link Keys in an LKPS Concept Lattice -- 1 Introduction -- 2 The Discovery of Link Keys with Pattern Structures -- 2.1 A Definition of Link Keys -- 2.2 A Pattern Structure for Link Key Discovery -- 3 The Pruning of an lkps-lattice -- 3.1 Correction and Completeness of a Link Key Candidate -- 3.2 Sandwich: An Algorithm for Selecting the Most Relevant Link Key Candidates -- 4 Discussion and Conclusion -- References -- Decision Concept Lattice vs. Decision Trees and Random Forests -- 1 Introduction -- 2 Basic Definitions -- 3 Construct a Concept Lattice via a Set of Decision Trees -- 4 Decision Lattice -- 5 Experiments -- 6 Conclusions -- References -- Exploring Scale-Measures of Data Sets -- 1 Introduction -- 2 Scales and Measurement -- 3 Ideals in the Lattice of Closure Systems -- 4 Recommending Conceptual Scale-Measures -- 5 Related Work -- 6 Conclusion -- References -- Filters, Ideals and Congruences on Double Boolean Algebras -- 1 Introduction -- 2 Concepts, Protoconcepts and Double Boolean Algebras -- 3 Filters and Ideals of a Double Boolean Algebra -- 4 Congruence on Double Boolean Algebras -- 5 Conclusion -- References -- Diagrammatic Representation of Conceptual Structures -- 1 Introduction -- 2 FCA and SCA Notions -- 3 Tabular, Euler and Hasse Diagrams."]
[{"$nulls":4},"4 Obtaining an Observationally Efficient Diagram -- 5 Conclusion -- References -- Author Index."]