Buch, Englisch, Band 8722, 302 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 493 g
16th International Conference, AIMSA 2014, Varna, Bulgaria, September 11-13, 2014, Proceedings
Buch, Englisch, Band 8722, 302 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 493 g
Reihe: Lecture Notes in Computer Science
ISBN: 978-3-319-10553-6
Verlag: Springer International Publishing
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 from 53 submissions. The range of topics is almost equally broad, from traditional areas such as computer vision and natural language processing to emerging areas such as mining the behavior of Web-based communities.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Spracherkennung, Sprachverarbeitung
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
Weitere Infos & Material
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.
