All Stories

  1. Automated Creation of a Legal Knowledge Graph Addressing Cases of Violence Against Women. Resource Methodology and Lessons Learned
  2. Learning Interpretable Probabilistic Models and Schema Axioms for Knowledge Graphs
  3. LP-DIXIT: Evaluating Explanations for Link Predictions on Knowledge Graphs using Large Language Models
  4. On the legal implications of Large Language Model answers: A prompt engineering approach and a view beyond by exploiting Knowledge Graphs
  5. Additive Counterfactuals for Explaining Link Predictions on Knowledge Graphs
  6. Explanation of Link Predictions on Knowledge Graphs via Levelwise Filtering and Graph Summarization
  7. Knowledge Graphs
  8. An Approach Based on Semantic Similarity to Explaining Link Predictions on Knowledge Graphs
  9. An unsupervised approach to disjointness learning based on terminological cluster trees
  10. Correction to: The Semantic Web: ESWC 2021 Satellite Events
  11. Class expression induction as concept space exploration: From DL-Foil to DL-Focl
  12. Machine Learning for the Semantic Web: Lessons learnt and next research directions
  13. Constructing Metrics for Evaluating Multi-Relational Association Rules in the Semantic Web from Metrics for Scoring Association Rules
  14. Boosting DL Concept Learners
  15. Adaptive Knowledge Propagation in Web Ontologies
  16. Approximate classification with web ontologies through evidential terminological trees and forests
  17. A Framework for Tackling Myopia in Concept Learning on the Web of Data
  18. Comparing Rule Evaluation Metrics for the Evolutionary Discovery of Multi-relational Association Rules in the Semantic Web
  19. DLFoil: Class Expression Learning Revisited
  20. Journal Track Chairs' Welcome & Organization
  21. Tree-based models for inductive classification on the Web Of Data
  22. An evolutionary algorithm for discovering multi-relational association rules in the semantic web
  23. Multi-label Based Learning for Better Multi-criteria Ranking of Ontology Reasoners
  24. Terminological Cluster Trees for Disjointness Axiom Discovery
  25. Efficient energy-based embedding models for link prediction in knowledge graphs
  26. Discovering Similarity and Dissimilarity Relations for Knowledge Propagation in Web Ontologies
  27. Leveraging the schema in latent factor models for knowledge graph completion
  28. Ontology enrichment by discovering multi-relational association rules from ontological knowledge bases
  29. Approximating Numeric Role Fillers via Predictive Clustering Trees for Knowledge Base Enrichment in the Web of Data
  30. Evolutionary Discovery of Multi-relational Association Rules from Ontological Knowledge Bases
  31. Scalable Learning of Entity and Predicate Embeddings for Knowledge Graph Completion
  32. The Data Mining OPtimization Ontology
  33. Inductive Classification Through Evidence-Based Models and Their Ensembles
  34. On the Effectiveness of Evidence-Based Terminological Decision Trees
  35. The Semantic Web. Latest Advances and New Domains
  36. A Gaussian Process Model for Knowledge Propagation in Web Ontologies
  37. Inductive Reasoning and Machine Learning for the Semantic Web
  38. Semantic Knowledge Discovery and Data-Driven Logical Reasoning from Heterogeneous Data Sources
  39. Towards Evidence-Based Terminological Decision Trees
  40. Uncertainty Reasoning for the Semantic Web III
  41. Rank prediction for semantically annotated resources
  42. NUMERIC PREDICTION ON OWL KNOWLEDGE BASES THROUGH TERMINOLOGICAL REGRESSION TREES
  43. Mining Linked Open Data through Semi-supervised Learning Methods Based on Self-Training
  44. Towards Numeric Prediction on OWL Knowledge Bases through Terminological Regression Trees
  45. Message from the ICSC 2012 Workshop Co-Chairs
  46. Ontology-based semantic search on the Web and its combination with the power of inductive reasoning
  47. Induction of robust classifiers for web ontologies through kernel machines
  48. Mining the Semantic Web
  49. Semantic Knowledge Discovery from Heterogeneous Data Sources
  50. Learning probabilistic Description logic concepts
  51. Learning with Semantic Kernels for Clausal Knowledge Bases
  52. Prediction of class and property assertions on OWL ontologies through evidence combination
  53. DL-LINK: A CONCEPTUAL CLUSTERING ALGORITHM FOR INDEXING DESCRIPTION LOGICS KNOWLEDGE BASES
  54. Efficient Resource Retrieval from Semantic Knowledge Bases
  55. Machine Learning Methods for Ontology Mining
  56. Towards the induction of terminological decision trees
  57. A Refinement Operator Based Method for Semantic Grouping of Conjunctive Query Results
  58. Categorize by: Deductive Aggregation of Semantic Web Query Results
  59. Combining Semantic Web Search with the Power of Inductive Reasoning
  60. Fuzzy Clustering for Semantic Knowledge Bases
  61. Induction of Concepts in Web Ontologies through Terminological Decision Trees
  62. Inductive learning for the Semantic Web: What does it buy?
  63. Inductive reasoning and semantic web search
  64. Learning to Rank Individuals in Description Logics Using Kernel Perceptrons
  65. Recovering uncertain mappings through structural validation and aggregation with the MoTo system
  66. Towards Learning to Rank in Description Logics
  67. Metric-based stochastic conceptual clustering for ontologies
  68. Inductive Classification of Semantically Annotated Resources through Reduced Coulomb Energy Networks
  69. Inductive Query Answering and Concept Retrieval Exploiting Local Models
  70. Fuzzy Clustering for Categorical Spaces
  71. Approximate Classification of Semantically Annotated Web Resources Exploiting Pseudo-metrics Induced by Local Models
  72. Partitional Conceptual Clustering of Web Resources Annotated with Ontology Languages
  73. ReduCE: A Reduced Coulomb Energy Network Method for Approximate Classification
  74. INDUCTION OF CLASSIFIERS THROUGH NON-PARAMETRIC METHODS FOR APPROXIMATE CLASSIFICATION AND RETRIEVAL WITH ONTOLOGIES
  75. Non-parametric Statistical Learning Methods for Inductive Classifiers in Semantic Knowledge Bases
  76. Tractable Reasoning with Bayesian Description Logics
  77. Evolutionary Conceptual Clustering of Semantically Annotated Resources
  78. Instance-based retrieval by analogy
  79. Randomized metric induction and evolutionary conceptual clustering for semantic knowledge bases
  80. DL-FOIL Concept Learning in Description Logics
  81. Learning with Kernels in Description Logics
  82. Induction of Optimal Semantic Semi-distances for Clausal Knowledge Bases
  83. Conceptual Clustering Applied to Ontologies
  84. A Multi-relational Hierarchical Clustering Method for Datalog Knowledge Bases
  85. Query Answering and Ontology Population: An Inductive Approach
  86. Conceptual Clustering and Its Application to Concept Drift and Novelty Detection
  87. Evolutionary Clustering in Description Logics: Controlling Concept Formation and Drift in Ontologies