An Approach for Context-Aware Service Discovery and Recommendation

Given the large amount of existing services and the diversified needs nowadays, it is time-consuming for end-users to find appropriate services. To help end-users obtain their desired services, context-aware systems provide a promising way to automatically search and recommend services using a user´s context. However, existing context-aware techniques have limited support for dynamic adaption to newly added context types (e.g., location, time and activity). Due to the diversity of user´s environment, the available context types may change over time. It is challenging to anticipate a complete set of context types while we design a context aware system. In this paper, we propose a context modeling approach which can dynamically handle various context types and values. More specifically, we use ontologies to enhance the meaning of a user´s context values and automatically identify the relations among different context values. Based on the relations among context values, we capture the potential services which the user might need. A case study is conducted to evaluate the effectiveness of our approach. The results show that our approach can use contexts to find users´ needs and recommend their desired services with high precision and recall.