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Computer Information Systems and Industrial Management
This book constitutes the refereed proceedings of the 11th International Conference on Computer Information Systems and Industrial Management, CISIM 2012, held in Venice, Italy, in September 2012. The 35 revised full papers presented together with 2 keynote talks were carefully reviewed and selected from 80 submissions. The papers are organized in topical sections on security, access control and intrusion detection; pattern recognition and image processing; biometric applications; algorithms and data management; networking; and system models and risk assessment.
Perspectives on Ontology Learning
Perspectives on Ontology Learning brings together researchers and practitioners from different communities − natural language processing, machine learning, and the semantic web − in order to give an interdisciplinary overview of recent advances in ontology learning. Starting with a comprehensive introduction to the theoretical foundations of ontology learning methods, the edited volume presents the state-of-the-start in automated knowledge acquisition and maintenance. It outlines future challenges in this area with a special focus on technologies suitable for pushing the boundaries beyond the creation of simple taxonomical structures, as well as on problems specifically related to knowledge modeling and representation using the Web Ontology Language. Perspectives on Ontology Learning is designed for researchers in the field of semantic technologies and developers of knowledge-based applications. It covers various aspects of ontology learning including ontology quality, user interaction, scalability, knowledge acquisition from heterogeneous sources, as well as the integration with ontology engineering methodologies.
Semantic Data Mining
Ontologies are now increasingly used to integrate, and organize data and knowledge, particularly in data and knowledge-intensive applications in both research and industry. The book is devoted to semantic data mining – a data mining approach where domain ontologies are used as background knowledge, and where the new challenge is to mine knowledge encoded in domain ontologies and knowledge graphs, rather than only purely empirical data. The introductory chapters of the book provide theoretical foundations of both data mining and ontology representation. Taking a unified perspective, the book then covers several methods for semantic data mining, addressing tasks such as pattern mining, class...
Learning Structure and Schemas from Documents
The rapidly growing volume of available digital documents of various formats and the possibility to access these through Internet-based technologies, have led to the necessity to develop solid methods to properly organize and structure documents in large digital libraries and repositories. Due to the extremely large volumes of documents and to their unstructured form, most of the research efforts in this direction are dedicated to automatically infer structure and schemas that can help to better organize huge collections of documents and data. This book covers the latest advances in structure inference in heterogeneous collections of documents and data. The book brings a comprehensive view o...
AI*IA 2015 Advances in Artificial Intelligence
This book constitutes the refereed proceedings of the 14th International Conference of the Italian Association for Artificial Intelligence, A*IA 2015, held in Ferrara, Italy, in September 2015. The 35 full papers presented were carefully reviewed and selected from 44 submissions. The papers are organized in topical sections on swarm intelligence and genetic algorithms; computer vision; multi-agents systems; knowledge representation and reasoning; machine learning; semantic Web; natural language; and scheduling, planning and robotics.
IJCAI-91
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IJCAI
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Machine Learning
The Sixteenth International Conference on Machine Learning (ICML-99) was held June 27-30, 1999 in Bled, Slovenia. It was co-located with the Ninth International Workshop on Inductive Logic Programming (ILP-99). These are the papers from this conference covering topics on empirical, theoretical, and cognitive-modelling research in all areas of machine learning.
