Review Comment:
The language of the document should be improved. There are far too many language mistakes. For example just in the introduction: “Software was written by various programming languages …”, or “There have been much studies”. This is not proper English.
The notion of web service composition is introduced in section 1.1 and exemplified using a simple example. The authors don’t do the same with service verification. There is no explanation is understood by service verification, neither a simple example to illustrate the concept. It seems service verification is equivalent to service discovery?
According to the authors “Semantic Web Services is the software component that provides dynamic service discovery …”. Semantic web services are not a software component! They are about describing semantically the functional, non-functional and interface aspects of a service. Semantic Web Services platforms/implementations on the other hand are those that support service discovery, composition, invocation, etc.
The notion of ontology is introduced in Section 3. What is the rational of using both attributes and relations in the ontology. It is not clear when to use one and when the other.
The approached proposed in the paper is adopting OWL-S as a mechanism to model Semantic Web Services. What was the rational for choosing this approach for semantically modeling services? Would your approach for service composition and verification work with other semantic wen services frameworks? Why not using a more recent, lighter framework for semantic web service?
The model used for modeling QoS properties is extremely basic. It is using value pairs to described QoS aspects. How does this work when modeling QoS properties such as trust or security?
According to definition 3 a Semantic Web Service is an association between a web service and an ontology. Concepts from the ontology are used to describe the inputs and outputs. However it is not clear how a certain concept or set of concepts are attached to an input or output.
Example 4 describes the SightseeingCityService. Its web service has Sightseeing=1, City=1, respTime =5. How is this in accordance with Definition 2 where pre-conditions and effects need to be provided to mode a web service?
The introduced feature-based similarity is in my opinion not a good measurement for showing if two services are similar. Let’s take for example the following example: f = X and Y -> Z and g = X and Y -> not Z. Common part in this case is a=3, while different part is b=0. The feature-based similarity is in this case 3/3+0=1. The services have the highest similarity even though they are basically providing the exact opposition output of each other.
The ontology-based similarity is introduced but after, it is never used.
The logic-based similarity is also defined in a very controversial manner. Let’s take for example the following case: f = X1 and X2 and X3 … X10 -> Y and g = X1 and X2 and X3 … X10 -> Z. fg, which is defined as the rule having in the body the conjunction of all terms in the two constituent formulae and the disjunction of all terms in the constituent formulae will be in this case fg = X1 and X2 and X3 … X30 and X1 and X2 and X3 … X10 -> Y or Z which means fg = X1 and X2 and X3 … X30 -> Y or Z. The SemFe(f, fg) will have the common part a=10, while the different part will be b = |Y,Z|/2 = 2/2 = 1, and thus SemFe(f, fg) = 30/31. For SemFe(g, fg) we get the same value 10/11. Finally to compute SimLo(f,g) we get (SemFe(f, fg)/2 + SemFe(g, fg)/2 ) / 2 = 30/31 so basically 96% similarity. Now consider that Service 1 (formula f) attached is delivering a train ticket reservation given the user data as input. Service 2 (formula g) is about computing a credit score given the same data about the user. According to logic-based similarity the two services are 96% similar even though they do totally different things. One is about getting a train ticket, the other about computing a credit score.
In the conclusions part there is a strong statement that the proposed approach performs better in terms of expanded and visited nodes as well as processing time. However the evaluation section does not support this statement as there is no evaluation compared to related approaches.
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