Hai Zhuge – författare

Text summarization has been studied for over a half century, but traditional methods process texts empirically and neglect the fundamental characteristics and principles of language use and understanding. Automatic summarization is a desirable technique for processing big data. This reference summarizes previous text summarization approaches in a multi-dimensional category space, introduces a multi-dimensional methodology for research and development, unveils the basic characteristics and principles of language use and understanding, investigates some fundamental mechanisms of summarization, studies dimensions on representations, and proposes a multi-dimensional evaluation mechanism. Investigation extends to incorporating pictures into summary and to the summarization of videos, graphs and pictures, and converges to a general summarization method. Further, some basic behaviors of summarization are studied in the complex cyber-physical-social space. Finally, a creative summarization mechanism is proposed as an effort toward the creative summarization of things, which is an open process of interactions among physical objects, data, people, and systems in cyber-physical-social space through a multi-dimensional lens of semantic computing. The author's insights can inspire research and development of many computing areas.

Classifying objects into categories at different granularity levels, establishing links between known objects, and discovering clues between known and unknown objects are essential for new-generation semantic data models. This book introduces the Resource Space Model (RSM), which effectively organizes and correctly manages resources by normalizing classification semantics.

This volume presents basic models of RSM and the Semantic Link Network (SLN), the relationship between the two, and an approach to integrating the two models and exploring their semantic-rich interconnection. Also detailed is a comprehensive theory of query operations on RSM and extensive coverage of the distributed RSM in parallel with the distributed relational database systems.

This text is sure to be considered a substantial contribution to the field of Knowledge Grid by researchers in the areas of web, semantic web, and decentralized data engineering, as well as the emerging semantic and knowledge grid arena.

This book explores next-generation artificial intelligence based on the symbiosis between humans, machines and nature, including the rules and emerging patterns of recognition, and the integration and optimization of various flows through cyberspace, physical space and social space. It unveils a reciprocal human-machine-nature symbiotic mechanism together with relevant rules on structuring and evolving reality, and also proposes a multi-dimensional space for modelling reality and managing the methodologies for exploring reality. As such it lays the foundation for the emerging research area cyber-physical-social intelligence.  Inspiring researchers and university students to explore the development of intelligence and scientific methodology, it is intended for researchers and broad readers with a basic understanding of computer science and the natural sciences.

Next-generation artificial intelligence will extend machine intelligence and human intelligence to cyber-physical-social intelligence rendered by various interactions in cyberspace, physical space and social space. With the transformational development of science and society, a multi-dimensional reality is emerging and evolving, leading to the generation and development of various spaces obeying different principles. A fundamental scientific challenge is uncovering the essential mechanisms and principles that structure and evolve the reality emerging and evolving along various dimensions. Meeting this challenge requires identifying the basic relations between humans, machines and nature in order to reveal the cyber-physical-social principles.