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Interdisciplinarity is a sine qua non condition for any modern endeavour, a reason for the International Conference on Interdisciplinary Studies (ICIS 2016) to promote new and emerging research topics and interdisciplinary collaborations. During the event experiences about how interdisciplinary research is carried out were summarized and the demand for interdisciplinary research and innovation was investigated. The 2016 edition aimed also to get an in-depth view of the solutions to provide the skills required for real advancement of our society, to emphasize the social need for creative thinking and innovation and to investigate the role creative thinking plays in producing new, integrative knowledge. The present volume summarizes the most relevant papers accepted for presentation during ICIS 2016, held at Ovidius University of Constanta, Romania, between 10 and 11 June 2016.

Physical Sciences, Engineering and Technology --- Technology --- Knowledge Engineering --- Knowledge Representation

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This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.

Natural Language Processing (NLP) --- Computational Linguistics --- Artificial Intelligence --- Data Mining and Knowledge Discovery --- Open Access --- Deep Learning --- Representation Learning --- Knowledge Representation --- Word Representation --- Document Representation --- Big Data --- Machine Learning --- Natural Language Processing --- Natural language & machine translation --- Computational linguistics --- Artificial intelligence --- Data mining --- Expert systems / knowledge-based systems