Intelligent Information Processing IV, 2008 5th IFIP International Conference on Intelligent Information Processing, October 19-22, 2008, Beijing, China IFIP Advances in Information and Communication Technology Series, Vol. 288

Knowledge existing in modern information systems usually comes from many sources and is mapped in many ways. There is a real need for representing ?knowledge pieces? as rather universal objects that should fit to multi-purpose a- ing systems. According to great number of information system?s tasks, knowledge representation is more or less detailed (e.g. some level of its granularity is - sumed). The main goal of this paper is to present chosen aspects of expressing granularity of knowledge implemented in intelligent systems. One of the main r- sons of granularity phenomena is diversification of knowledge sources, therefore the next section is devoted to this issue. 2. Heterogeneous Knowledge as a Source for Intelligent Systems Knowledge, the main element of so-called intelligent applications and systems, is very often heterogeneous. This heterogeneity concerns the origin of knowledge, its sources as well as its final forms of presentation. In this section the selected c- teria of knowledge differentiation will be presented, in the context of potential sources of knowledge acquisition. In Fig. 1 an environment of intelligent systems is shown, divided into different knowledge sources for the system. Fig. 1. Potential knowledge sources for intelligent information/reasoning system. Source: own elaboration based on (Mach, 2007) p. 24.

Keynote Presentations.- Semantic Computing.- Towards Brain-inspired Web Intelligence.- Data Mining Technologies Inspired from Visual Principle.- Semantic Web Services.- A Context Model for Service Composition Based on Dynamic Description Logic.- Evaluation of Ontologies and DL Reasoners.- ER2OWL: Generating OWL Ontology from ER Diagram.- Knowledge Acquisition and Management.- Voice knowledge acquisition system for the management of cultural heritage.- Granularity of Knowledge from Different Sources.- Fuzzy Ontology Models Based on Fuzzy Linguistic Variable for Knowledge Management and Information Retrieval.- Data Mining.- Blog Classification: Adding Linguistic Knowledge to Improve the K-NN Algorithm.- A Modified Clustering Method with Fuzzy Ants.- An New Algorithm for Modeling Regression Curve.- Web Search.- Enhancing Web Search with Heterogeneous Semantic Knowledge.- Exploring Words with Semantic Correlations from Chinese Wikipedia.- A Heuristic Knowledge Reduction Algorithm Based on Partition Subdivision and Consistent Degree.- Cognition-based Intelligent Information Processing.- Object-based Image Retrieval with Attention Analysis and Spatial Re-ranking.- Forecasting Stock Exchange Movements Using Artificial Neural Network Models and Hybrid Models.- A Robot Emotion Generation Mechanism Based on PAD Emotion Space.- Study of Personalized Network Tutoring System Based on Emotional-cognitive Interaction.- Image Processing.- A Novel Fingerprint Matching Method Combining Geometric and Texture Features.- Distinctive Image Region Features from Color Invariant Moments.- Inter-video Similarity for Video Parsing.- Image Segmentation of Historical Handwriting from Palm Leaf Manuscripts.- Virtual Organization and Applications.- Virtual Organizations: Trends and Models.- A Surveyof UML Based Regression Testing.- Virtual Organizations: An Overview.- Risk Management and Computational Linguistics.- A Risk Assessment System with Automatic Extraction of Event Types.- Addressing Risk Assessment for Patient Safety in Hospitals through Information Extraction in Medical Reports.- An SMS-based System Architecture (Logical Model) to Support Management of Information Exchange in Emergency Stuations. poLINT-112-SMS PROJECT.- Semi Automatic Ontology Instantiation in the domain of Risk Management.

The papers in this volume were peer-reviewed and carefully selected Much information in this series is published in advance of journal publication The contributors in this volume are world-renowned experts in their field Includes supplementary material: sn.pub/extras