Similarity Search for Web Services

Abstract

Web services are loosely coupled software components, published, located, and invoked across the web. The growing number of web services available within an organization and on the Web raises a new and challenging search problem: locating desired web services. Traditional keyword search is insufficient in this context: the specific types of queries users require are not captured, the very small text fragments in web services are unsuitable for keyword search, and the underlying structure and semantics of the web services are not exploited. We describe the algorithms underlying the Woogle search engine for web services. Woogle supports similarity search for web services, such as finding similar webservice operations and finding operations that compose with a given one. We describe novel techniques to support these types of searches, and an experimental study on a collection of over 1500 web-service operations that shows the high recall and precision of our algorithms.

Automatic Web Service Tagging Using Machine Learning and WordNet Synsets

“…In [13], a service request and a service are represented as two finite state machines then they are compared using various heuristics to find structural similarities between them. In [8], the Woogle web service search engine is presented, which takes the needed operation as input and searches for all the services that include an operation similar to the requested one. In [3], tags coming from folksonomies are used to discover and compose services.…”

Humans, semantic services and similarity: A user study of semantic Web services matching and composition

“…While interesting results were available for retrieval of non-Semantic Web services [16], they lack formal semantics, making them insufficient for automated service composition. Therefore, we limit the scope of this article to Semantic Web services.…”

Leveraging Web Services Discovery with Customizable Hybrid Matching

“…The main drawback of this method is that poor, unnormalized heuristics (such as matching scores of 5 or 10) in assigning weights for term similarity are used. Dong et al [9] present a search engine focused on retrieval of WSDL operations. The underlying assumption of their method is that parameters tend to reflect the same concept if they often occur together.…”