Cooperative tasks to be successful in Collaborative Distributed Environments (CDE) require from users to be known. Before hard, which users are more suitable in the system to cooperate with, as well as which tools are needed to achieve the common goal in the system in a cooperative way. On the other hand, awareness allows users to be aware of others’ activities each and every moment. Information about others’ activities combined with their intentions and purposes could be used to improve cooperation in CDEs. This paper focuses on associating the concept of awareness with vector quantization techniques. It presents a novel non-supervised Artificial Neural Network (ANN) based model for CDE named CAwANN, which uses the information of awareness collaborations occurring in the environment in order to achieve the most suitable awareness-based collaboration / cooperation in the environment.
Cooperative tasks to be successful in Collaborative Distributed Environments (CDE) require from users to be known. Before hard, which users are more suitable in the system to cooperate with, as well as which tools are needed to achieve the common goal in the system in a cooperative way. On the other hand, awareness allows users to be aware of others’ activities each and every moment. Information about others’ activities combined with their intentions and purposes could be used to improve cooperation in CDEs. This paper focuses on associating the concept of awareness with vector quantization techniques. It presents a novel non-supervised Artificial Neural Network (ANN) based model for CDE named CAwANN, which uses the information of awareness collaborations occurring in the environment in order to achieve the most suitable awareness-based collaboration / cooperation in the environment. Read More
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