Opinion based service selection in a pervasive cooperative consumer network

Of late, an easy access to the Web 2.0 applications through the hand-held mobile devices has provided the consumers with the opportunity to express opinions on their invoked services conveniently. These opinions, also known as the Internet word of mouth, often impact a potential consumer´s service selection notably in service rich urban terrains. Access to these opinions involves tariffs since they are available over the Internet. In addition, individual analysis of such opinions is inconvenient due to mobile devices´ inherent limitations. However, a `pervasive cooperative consumer network´ can be employed using consumers´ connectivity enabled mobile devices to share and acquire service related opinions at no monetary cost. Yet, this network, realized over an underlying mobile ad hoc network, does not consider inclusion of the opinions for service selection. Therefore, we propose a service selection framework to integrate opinions with the widely used minimum hop count method for service selection. The opinions are first clustered using the Wordnet-based K-means clustering algorithm and then quantified using the Sentiwordnet scores to be automatically included in the framework. The proposal is further supported by the simulation results.