Artificial Intelligence: Methodology, Systems, and Applications 16th International Conference, AIMSA 2014, Varna, Bulgaria, September 11-13, 2014. Proceedings /

• Corporate Author: SpringerLink (Online service)
• Other Authors: Agre, Gennady (Editor), Hitzler, Pascal (Editor), Krisnadhi, Adila A. (Editor), Kuznetsov, Sergei O. (Editor)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2014.
• Series: Lecture Notes in Computer Science, 8722
• Subjects: Computer science.; Data mining.; Information storage and retrieval.; User interfaces (Computer systems).; Artificial intelligence.; Computer simulation.; Computer Science.; Artificial Intelligence (incl. Robotics).; Data Mining and Knowledge Discovery.; Information Storage and Retrieval.; Information Systems Applications (incl. Internet).; User Interfaces and Human Computer Interaction.; Simulation and Modeling.

This book constitutes the refereed proceedings of the 16th International Conference on Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 2014, held in Varna, Bulgaria in September 2014. The 14 revised full papers and 9 short papers presented were carefully reviewed and selected...

Table of Contents:

• Learning Probabilistic Semantic Network of Object-oriented Action and Activity
• Semantic-aware Expert Partitioning
• User-Level Opinion Propagation Analysis in Discussion Forum Threads
• Social News Feed Recommender
• Boolean Matrix Factorisation for Collaborative Filtering: An FCA-Based Approach
• Semi-Supervised Image Segmentation
• Analysis of Rumor Spreading in Communities Based on Modified SIR Model in Microblog
• Modeling a System for Decision Support in Snow Avalanche Warning
• Using Balanced Random Forest and Weighted Random Forest
• Applying Language Technologies on Healthcare Patient Records for Better Treatment of Bulgarian Diabetic Patients
• Incrementally Building Partially Path Consistent Qualitative Constraint Networks
• A Qualitative Spatio-Temporal Framework Based on Point Algebra
• Training Datasets Collection and Evaluation of Feature Selection Methods for Web Content Filtering
• Feature Selection by Distributions Contrasting
• Educational Data Mining for Analysis of Students' Solutions.