http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Modern Approaches for Intelligent Information and Database Systems
This book offers a unique blend of reports on both theoretical models and their applications in the area of Intelligent Information and Database Systems. The reports cover a broad range of research topics, including advanced learning techniques, knowledge engineering, Natural Language Processing (NLP), decision support systems, Internet of things (IoT), computer vision, and tools and techniques for Intelligent Information Systems. They are extended versions of papers presented at the ACIIDS 2018 conference (10th Asian Conference on Intelligent Information and Database Systems), which was held in Dong Hoi City, Vietnam on 19-21 March 2018. What all researchers and students of computer science need is a state-of-the-art report on the latest trends in their respective areas of interest. Over the years, researchers have proposed increasingly complex theoretical models, which provide the theoretical basis for numerous applications. The applications, in turn, have a profound influence on virtually every aspect of human activities, while also allowing us to validate the underlying theoretical concepts.
Part I: Knowledge Engineering and Semantic Web -- A Three-stage Consensus-based Method for Collective Knowledge Determination -- Fuzzy Ontology Modeling by Utilizing Fuzzy Set and Fuzzy Description Logic -- An Approach for Recommending Group Experts on Question and Answering Sites -- A method for uncertainty elicitation of experts using belief function -- Storing Hypergraph-based Data Models in Non-hypergraph Data Storage -- Part II: Natural Language Processing and Text Mining -- A Fuzzy Logic Approach to Predict the Popularity of a Presidential Candidate -- DNA Sequences Representation Derived from Discrete Wavelet Transformation for Text Similarity Recognition -- Tweet integration by ﬁnding the shortest paths on a word graph -- Event detection in Twitter: Methodological Evaluation and Structural Analysis of the Bibliometric Data -- Combination of inner approach and context-based approach for extracting feature of medical record data -- A Novel Method to Predict Type for DBpedia Entity -- Context-Based Personalized Predictors of the Length of Written Responses to Open-ended Questions of Elementary School Students -- Part III: Machine Learning and Data Mining -- Robust Scale-Invariant Normalization and Similarity Measurement for Time Series Data.
edited by Andrzej Sieminski, Adrianna Kozierkiewicz, Manuel Nunez, Quang Thuy Ha.
Studies in Computational Intelligence, 769