Innovations in Big Data Mining and Embedded Knowledge

Description

This book addresses the usefulness of knowledge discovery through data mining. With this aim, contributors from different fields propose concrete problems and applications showing how data mining and discovering embedded knowledge from raw data can be beneficial to social organizations, domestic spheres, and ICT markets. Data mining or knowledge discovery in databases (KDD) has received increasing interest due to its focus on transforming large amounts of data into novel, valid, useful, and structured knowledge by detecting concealed patterns and relationships. The concept of knowledge is broad and speculative and has promoted epistemological debates in western philosophies. The intensified interest in knowledge management and data mining stems from the difficulty in identifying computational models able to approximate human behaviors and abilities in resolving organizational, social, and physical problems. Current ICT interfaces are not yet adequately advanced to support and simulate the abilities of physicians, teachers, assistants or housekeepers in domestic spheres. And unlike in industrial contexts where abilities are routinely applied, the domestic world is continuously changing and unpredictable. There are challenging questions in this field: Can knowledge locked in conventions, rules of conduct, common sense, ethics, emotions, laws, cultures, and experiences be mined from data? Is it acceptable for automatic systems displaying emotional behaviors to govern complex interactions based solely on the mining of large volumes of data? Discussing multidisciplinary themes, the book proposes computational models able to approximate, to a certain degree, human behaviors and abilities in resolving organizational, social, and physical problems. The innovations presented are of primary importance for: a. The academic research community b. The ICT market c. Ph.D. students and early stage researchers d. Schools, hospitals, rehabilitation and assisted-living centers e. Representatives from multimedia industries and standardization bodies Front Matter ....Pages i-xix More Than Data Mining (Anna Esposito, Antonietta M. Esposito, Lakhmi C. Jain)....Pages 1-11 Designing a Recommender System for Touristic Activities in a Big Data as a Service Platform (Valerio Bellandi, Paolo Ceravolo, Ernesto Damiani, Eugenio Tacchini)....Pages 13-33 EML: A Scalable, Transparent Meta-Learning Paradigm for Big Data Applications (Uday Kamath, Carlotta Domeniconi, Amarda Shehu, Kenneth De Jong)....Pages 35-59 Towards Addressing the Limitations of Educational Policy Based on International Large-Scale Assessment Data with Castoriadean Magmas (Evangelos Kapros)....Pages 61-81 What Do Prospective Students Want? An Observational Study of Preferences About Subject of Study in Higher Education (Alessandro Vinciarelli, Walter Riviera, Francesca Dalmasso, Stefan Raue, Chamila Abeyratna)....Pages 83-97 Speech Pause Patterns in Collaborative Dialogs (Maria Koutsombogera, Carl Vogel)....Pages 99-115 Discovering Knowledge Embedded in Bio-medical Databases: Experiences in Food Characterization and in Medical Process Mining (Giorgio Leonardi, Stefania Montani, Luigi Portinale, Silvana Quaglini, Manuel Striani)....Pages 117-136 A Paradigm for Democratizing Artificial Intelligence Research (Erwan Moreau, Carl Vogel, Marguerite Barry)....Pages 137-166 Big Data and Multimodal Communication: A Perspective View (Costanza Navarretta, Lucretia Oemig)....Pages 167-184 A Web Application for Characterizing Spontaneous Emotions Using Long EEG Recording Sessions (Giuseppe Placidi, Luigi Cinque, Matteo Polsinelli)....Pages 185-202 Anticipating the User: Acoustic Disposition Recognition in Intelligent Interactions (Ronald Böck, Olga Egorow, Juliane Höbel-Müller, Alicia Flores Requardt, Ingo Siegert, Andreas Wendemuth)....Pages 203-233 Humans Inside: Cooperative Big Multimedia Data Mining (Shahin Amiriparian, Maximilian Schmitt, Simone Hantke, Vedhas Pandit, Björn Schuller)....Pages 235-257 Conversational Agents and Negative Lessons from Behaviourism (Milan Gnjatović)....Pages 259-274 Back Matter ....Pages 275-276