Aiping Li

Yan Jia

Zhaoquan Gu

Knowledge representation is an important task in understanding how humans think and learn. Although many representation models or cognitive models have been proposed, such as expert systems or knowledge graphs, they cannot represent procedural knowledge, i.e., dynamic knowledge, in an efficient way. This book introduces a new knowledge representation model called MDATA (Multi-dimensional Data Association and inTelligent Analysis). By modifying the representation of entities and relations in knowledge graphs, dynamic knowledge can be efficiently described with temporal and spatial characteristics. The MDATA model can be regarded as a high-level temporal and spatial knowledge graph model, which has strong capabilities for knowledge representation. This book introduces some key technologies in the MDATA model, such as entity recognition, relation extraction, entity alignment, and knowledge reasoning with spatiotemporal factors. The MDATA model can be applied in many critical applications and this book introduces some typical examples, such as network attack detection, social network analysis, and epidemic assessment. The MDATA model should be of interest to readers from many research fields, such as database, cyberspace security, and social network, as the need for the knowledge representation arises naturally in many practical scenarios.

Theory, Methods and Applications

MDATA: A New Knowledge Representation Model

Francis C.M. Lau

Yuexuan Wang

Qiang-Sheng Hua

This book introduces novel solutions to the rendezvous problem in distributed systems, a fundamental problem that underpins the construction of many important functions in distributed systems and networks. The book covers rendezvous theories, distributed rendezvous algorithms, and rendezvous applications in practical systems, presents state-of-the-art rendezvous results and highlights the latest methods of rendezvous in distributed systems. It provides in particular an in-depth treatment of the blind rendezvous and oblivious blind rendezvous problems and their solutions. Further, it sheds new light on rendezvous applications in cognitive radio networks and rendezvous search in graphs. As such, it will also be of interest to readers from other research fields such as robotics, wireless sensor networks, and game theory.

Theory, Algorithms and Applications

Rendezvous in Distributed Systems

Zhaoquan Gu

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