1. ferdowsi University of Mashhad 1 Automatic Semantic Web Service Composition based on owl-s Research Proposal presented by : Toktam ghafarian

2. ferdowsi University of Mashhad 2 Semantic web service composition Semantic web service (SWS) composition process is generally performed when no available atomic or composite service can satisfy the required request and a combination which can satisfy request can be generated from available atomic or composite services. The required request contains a set of available input parameters and a set of wanted output parameters. The sequential execution of these services provides the requested functionality.

3. ferdowsi University of Mashhad 3 Decision tree of AI solution for sws composition approach

4. ferdowsi University of Mashhad 4 Semantic similarity it is necessary to determine the level of semantic closeness between a set of Service Outputs and a corresponding set of Service Inputs.

5. ferdowsi University of Mashhad 5 Semantic similarity (definition 1) Similarity of concept A, concept B is computed as

6. ferdowsi University of Mashhad 6 Semantic similarity (definition 2) Similarity of concept A, concept B is computed as

7. ferdowsi University of Mashhad 7 Semantic similarity (definition3) If C1 and C2 are the same concepts then the similarity degree of the match is called “exact match”. If there is an already available mapping from C2 to C1, then similarity degree is considered as “maps match”. If C2 inherits C1, but hierarchy path is of more than one level, then similarity degree between them is considered as “plugin match”. if C1 inheritsC2, then the similarity degree is considered as “subsume match”. If there is not any hierarchy relation between concepts, then attribute similarity is considered.  If C1 and C2 have some common/similar attributes then these concepts are considered as partially overlapping and the similarity degree of match is “intersection match”. If there is not any hierarchy and parameter similarity, then these concepts are considered as unmatched and their similarity degree becomes “disjoint match”.

8. ferdowsi University of Mashhad 8 SWS composition If a parameter x of a service is annotated with A and a value y annotated with B is available, we can set x = y and call the service only if subsumes(A,B) holds a composition request R always consists of a set of available input concepts R.in and a set of requested output concepts R.out. A composition algorithm discovers a (topologically sorted) set of n services

9. ferdowsi University of Mashhad 9 SWS composition For each composition solving the request R, isGoal(S) will hold:

10. ferdowsi University of Mashhad 10 Some of Different approaches to sws composition AI planning Graph based planning  Graph plan Uninformed approaches  it build such an composition algorithm based on iterative deepening depth-first search.  Algorithm builds a valid web service composition starting from the back. An Informed (Heuristic approach)  In an informed search, a heuristic c helps to decide which nodes are to be expanded next.

11. ferdowsi University of Mashhad 11 a sws composition example

12. ferdowsi University of Mashhad 12 Sws using graphplan

13. ferdowsi University of Mashhad 13 Uninformed approach

14. ferdowsi University of Mashhad 14 Informed approach

15. ferdowsi University of Mashhad 15 Different approaches to sws composition An evolutionary composition approach  GA use (variable-length) strings of service identifiers which can be processed by standard genetic algorithms. it uses a specialized mutation operation that can make the search more efficient.  Ant colony An ant colony appraoch have not been use to compose sws until now

16. ferdowsi University of Mashhad 16 Research proposal Use service profile of any semantic web service that is specified in owl-s for semantic similarity Use of ant colony optimization method to automatic construct a sws composition from a set of desired output request and available input request