The 3rd International Workshop on Intelligent Data Analysis and Management

ISBN-13: 9789400792869 / Angielski / Miękka / 2015 / 132 str.

Lorna Uden; Leon S. L. Wang; Tzung-Pei Hong

Opis

These papers on Intelligent Data Analysis and Management (IDAM) examine issues related to the research and applications of Artificial Intelligence techniques in data analysis and management across a variety of disciplines.

Spis treści

An Information Quality (InfoQ) Framework for Ex-Ante and Ex-Post Evaluation of Empirical Studies; G. Shmueli, R. Kenett.- Memory-Aware Mining of Indirect Associations over Data Streams; W.-Y. Lin et al.- Graph-based batch mode active learning; C.H. Park.- One Pass Outlier Detection for Streaming Categorical Data; S.C.  Tan et al.- Measuring of QoE for Cloud Applications; Y.-H. Tao et al.- Mining Weighted Partial Periodic Patterns; K.-J. Yang et al.- Edge Selection for Degree Anonymization on K Shortest Paths; S.-L. Wang et al.- K-Neighborhood Shortest Path Privacy in the Cloud; S.-L. Wang et al.- The Framework of Information Processing Network for Supply Chain Innovation in Big Data Era; C.-H. Chao.- Website Navigation Recommendation Based on Reinforcement Learning Technique; Y.-L. Tang et al.- An Approach for Hate Groups Detection in Facebook; I-H. Ting et al.- Toward Crowdsourcing Data Mining; H.-C. Yang, C.-H. Lee.- Wireless Security Analysis Using War Drive Investigation in Kaohsiung Areas; H. Hsiao et al.- Guanxi buying in the social media environment; C. Lin, S. Lu.- Introspection of unauthorized sharing on social networking sites; C. Lin and T.-Y. Lin.

Blurb

These papers on Intelligent Data Analysis and Management (IDAM) examine issues related to the research and applications of Artificial Intelligence techniques in data analysis and management across a variety of disciplines. The papers derive from the 2013 IDAM conference in Kaohsiung ,Taiwan. It is an interdisciplinary research field involving academic researchers in information technologies, computer science, public policy, bioinformatics, medical informatics, and social and behavior studies, etc. The techniques studied include (but are not limited to): data visualization, data pre-processing, data engineering, database mining techniques, tools and applications, evolutionary algorithms, machine learning, neural nets, fuzzy logic, statistical pattern recognition, knowledge filtering, and post-processing, etc.