A similarity measure for the negotiation in web services

A Service Discovery Approach Based on a Quantitative Similarity Measure for M-Tourism Platforms

“…To manage the communication between clients and the SLC, we propose a SIP extension. This extension is materialized by adding new methods like "REQ" and "REQdev" as well as response codes like "201" and "202" [14].…”

“…Several similarity measures were proposed in various applications fields like similarity for textual data [29,30], similarity for intrusion detection [31] and similarity for Web services discovery [14].…”

“…To evaluate the similarity between two profiles (for example service and user), we have to define a descriptive common form for all profiles. Each profile is described by m characteristics (X 1 , X 2 ···X m ) and represented by a binary vector including the existence of each descriptor such as: In [14], we have used the Jaccard Similarity Measure (JSM) to discover services in an e-commerce platform. The JSM state as follows:…”

“…The Quantitative Similarity Measure (QSim) is proposed in order to fill in the weaknesses of the JSM, detected in our previous work [14]. Among these weaknesses, we have noticed that JSM checks just the existence of a characteristic (we have a binary result: 1 if the parameter exists, 0 else).…”

“…Even if with the JSM, used in [14], the degree of similarity between the two objects is of 100%, it is obvious that the two objects are not completely identical.…”