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Knowledge Representation and Reasoning.- Deduction in Existential Conjunctive First-Order Logic: An Algorithm and Experiments.- Use-Based Discovery of Pervasive Services.- Expressive Approximations in DL-Lite Ontologies.- Reasoning Mechanism for Cardinal Direction Relations.- A Framework for Time-Series Analysis.- Intelligent Techniques for Adaptation, Personalization, and Recommendation.- Cross-Language Personalization through a Semantic Content-Based Recommender System.- Towards Effective Recommendation of Social Data across Social Networking Sites.- Term Ranking and Categorization for Ad-Hoc Navigation.- Time Optimized Algorithm for Web Document Presentation Adaptation.- Constraints and Search.- Discrepancy-Based Sliced Neighborhood Search.- Constraint Models for Reasoning on Unification in Inductive Logic Programming.- Coalition Structure Generation with GRASP.- Machine Learning, Data Mining, and Information Retrieval.- A Bayesian Model for Entity Type Disambiguation.- The Impact of Valence Shifters on Mining Implicit Economic Opinions.- Entity Popularity on the Web: Correlating ANSA News and AOL Search.- Using Machine Learning to Prescribe Warfarin.- Single-Stacking Conformity Approach to Reliable Classification.- A Relative Word-Frequency Based Method for Relevance Feedback.- AI in Education.- Sequence Detection for Adaptive Feedback Generation in an Exploratory Environment for Mathematical Generalisation.- A Deep Insight in Chat Analysis: Collaboration, Evolution and Evaluation, Summarization and Search.- Ontology-Based Authoring of Intelligent Model-Tracing Math Tutors.- Applications.- Comparative Analysis of Distributed, Default, IC, and Fuzzy ARTMAP Neural Networks for Classification of Malignant and Benign Lesions.- An Adaptive Approach for Integration Analysis of Multiple Gene Expression Datasets.- EVTIMA: A System for IE from Hospital Patient Records in Bulgarian.- Direct Field Oriented Neural Control of a Three Phase Induction Motor.- General Shape Analysis Applied to Stamps Retrieval from Scanned Documents.- Posters.- Selection of Foundational Ontology for Collaborative Knowledge Modeling in Healthcare Domain.- Towards Ontological Blending.- Integration of Ontology with Development of Personalized E-Learning Facilities for Dyslexics.- A Meta Learning Approach: Classification by Cluster Analysis.- Mapping Data Driven and Upper Level Ontology.- Data Sample Reduction for Classification of Interval Information Using Neural Network Sensitivity Analysis.- Individualized Virtual Humans for Social Skills Training.- Signal Classification with Self-organizing Mixture Networks.- Simulation of the Autonomous Agent Behavior by Autoregressive Models.- Semi-partitioned Horn Clauses: A Tractable Logic of Types.- Feed Rate Profiles Synthesis Using Genetic Algorithms.- An Ontology of All of Computing: An Update on Challenges and Approaches.
The 14th International Conference on Artificial Intelligence: Methodology, Systems, Applications (AIMSA 2010) was held in Varna, Bulgaria, during September 8-10, 2010. The AIMSA conference series has provided a biennial forum for the presen- tion of artificial intelligence research and development since 1984. The conference covers the full range of topics in artificial intelligence (AI) and related disciplines and provides an ideal forum for international scientific exchange between Central/Eastern Europe and the rest of the world. The 2010 AIMSA edition continued this tradition. For AIMSA 2010, we decided to place special emphasis on the application and leverage of AI technologies in the context of knowledge societies where knowledge creation, accessing, acquiring, and sharing empower individuals and communities. A number of AI techniques play a key role in responding to these challenges. AI is - tensively used in the development of systems for effective management and flexible and personalized access to large knowledge bases, in the Semantic Web technologies that enable sharing and reuse of and reasoning over semantically annotated resources, in the emerging social Semantic Web applications that aid humans to collaboratively build semantics, in the construction of intelligent environments for supporting (human and agent) learning, etc. In building such intelligent applications, AI techniques are typically combined with results from other disciplines such as the social sciences, distributed systems, databases, digital libraries, information retrieval, service-oriented applications, etc.