Artificial intelligence methodology, systems, and applications : 16th International Conference, AIMSA 2014, Varna, Bulgaria, September 11-13, 2014. Proceedings /
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...
| Corporate Authors: | International Conference on Artificial Intelligence: Methodology, Systems, Applications Varna, Bulgaria) |
|---|---|
| Other Authors: | International Conference on Artificial Intelligence: Methodology, Systems, Applications, Agre, Gennady,, Hitzler, Pascal,, Krisnadhi, Adila A.,, Kuznetsov, Sergei O.,, SpringerLink (Online service) |
| Format: | eBook |
| Language: | English |
| Published: |
Cham :
Springer,
2014.
|
| Physical Description: |
1 online resource (xix, 302 pages) : illustrations. |
| Series: |
Lecture notes in computer science. Lecture notes in artificial intelligence ;
8722. LNCS sublibrary. Artificial intelligence. |
| Subjects: |
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.