Event-Driven Semantic Service Discovery Based on Word Embeddings

Abstract

Service discovery is vital to event handling in Internet of Things applications which are based on the event-driven service-oriented architecture. However, in service discovery, the problem of service matching that establishes relationships between services and events has been seldom investigated through a semantic way. In this paper, to facilitate the efficiency of service discovery triggered by events, we propose a novel method of semantic service matching based on word embeddings. In this method, two types of semantic services about events (i.e., event-recognition services and event-handing services) are specified and matched through semantic similarity assessment that is conducted with word embeddings. Besides, to obtain high-quality word embeddings, we present a hybrid approach for learning word embedding which treats words in distinct means according to word frequency. Experiments demonstrated on different data sets show that our method of semantic service matching is an effective way to facilitate event-driven service discovery, and the proposed training approach for word embeddings outperforms existing works and is able to improve the accuracy of event-driven service discovery.