Abstract
The lack of semantic parts, increasing the number of Web services in the Web, and syntactic-based search operation are the main problems of current Web service technologies, these factors make difficult for clients to find a required web service. This paper shows a matchmaking algorithm to discover Semantic Web Services that are satisfying client requirements. It depends on two factors that distinguish it from any conventional Web service discovery algorithm; the first one is using semantic matching technique to overcome shortcoming of keyword matching techniques, the second one is tying Quality of Service (QoS) metrics of Web Service (WS) with fuzzy words that are used in user’s request. At least fifty percent average gain in search relevancy is obtained when our matchmaking algorithm is applied to WSs that are actually matching the chosen fuzzy semantic theme.
Highlights
One of the crucial steps in an efficient Web service search is to understand what users mean in their request
All Web Service (WS) in the domain of books will be examined one by one to get WSs that fit to Y part, three matching types will be performed from inputs to outputs of each, any WS has similarity value is equal or greater than θ2 will be stored in list of related WSs (LRWS) they will be ranked according level of Quality of Service (QoS) metric(s) that user needs (X part). any used hedge should be taken into account
The dataset that will be discovered has 64 WSs in books domain, the Actual Related WSs (ARWs) that match with the Y part semantically or syntactically or both and they should be appeared in search result equal 16 WSs, the rest of WSs (i.e., 48) will be Actual Unrelated WSs (AUWs) that should not be in the result of Y part, both values will be used to determine relevance and irrelevance ratio respectively as the following: Relevance ratio no. of related WSs / no. of ARWs 100%, Irrelevance ratio
Summary
One of the crucial steps in an efficient Web service search is to understand what users mean in their request. The current popular search engines literally take the search input without much semantic interpretation and attempt to find WS that may contain all or some of the keywords in the input query This sometimes leads to the inclusion of WS that are not relevant to the user’s request in the returned search result. The services developed with such technologies are called Semantic Web Services (SWS) [811] respectively These technologies provide means of describing in detail the service capabilities, execution flows, policies and other related information. These technologies have given a new boost to service discovery and service composition research as new fields for experimentation have emerged [12]. Matchmaking of semantic service descriptions is a key technique for realizing discovery that aims at judging whether a located service is relevant compared to a given request [13]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
