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OPOSSUM: Object-PrOcess Structural / Semantic Unified Matching

OPOSSUM: Object-PrOcess Structural / Semantic Unified Matching. Eran Toch. Instructors: Prof. Dov Dori & Dr. Iris Reinhartz-Berger In collaboration with Dr. Pnina Soffer. Second OPM Workshop – October 2004. Technion – Israel Institute of Technology

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OPOSSUM: Object-PrOcess Structural / Semantic Unified Matching

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  1. OPOSSUM: Object-PrOcess Structural / Semantic Unified Matching Eran Toch Instructors: Prof. Dov Dori & Dr. Iris Reinhartz-Berger In collaboration with Dr. Pnina Soffer Second OPM Workshop – October 2004 Technion – Israel Institute of Technology Faculty of Industrial Engineering and Management Technion – Israel Institute of Technology

  2. Agenda • OPM/S Framework • Motivation and Challenges • OPOSSUM – A Search Engine for SWS: • An Example • Capability Equivalence • Algorithm Description • Evaluation • Summary and Contribution Technion – Israel Institute of Technology

  3. OPM/S • Provide human-accessible and efficient methods for searching and modeling semantic web services, based on Object-Process Methodology. • The work consist of the following components: Technion – Israel Institute of Technology

  4. What we need? A method to search through large repositories of OWL-S and OPM/S models and to retrieve matching services. Technion – Israel Institute of Technology

  5. Challenges • Differences in abstraction levels (We want to get the relevant models, no matter the extent in which they are detailed). • Partial Results (If a certain model supports only 50% of our requirements, we may still be able to reuse it). • Performance: Number of services must be scale-free. • Precision vs. Recall (how many un-relevant models do we agree to get in order to get all relevant ones?) Technion – Israel Institute of Technology

  6. Current Solutions • Woogle [3] • Web Service Composer [2] • Semantic Web Service Composer (from IBM Research) [4] Technion – Israel Institute of Technology

  7. About OPOSSUM A search engine for OPM/S specifications Technion – Israel Institute of Technology

  8. About OPOSSUM – cont’d • Overcomes: • Differences in abstraction levels • Sub models • Partial matching • Performance is achieved using a pre-indexing stage. • OWL-S specifications are scanned by using the automatic translation into OPM/S. • OPM/S models do not contain every possible OPM model, only those with O(1) ending points. Technion – Israel Institute of Technology

  9. OPOSSUM – An Example External Services are notated as environmental OPOSSUM searches for a service that will implement all possible combinations of external services Technion – Israel Institute of Technology

  10. OPOSSUM - An Example, cont’d Query Model (Q) Set of Target Models (M) OPOSSUM calculates the Capability Equivalence (CP) value between Q and the set of target models Technion – Israel Institute of Technology

  11. Capability Equivalence • CP Represents the extent to which a target model (T) can be reused instead of a query model (Q): 0.8 0.2 0.2 Technion – Israel Institute of Technology

  12. Algorithm • General sketch of CP’s calculation algorithm: • Pre-Indexing • Crawls over OPM/S specifications. • Calculating and indexing semantic similarity • Converting target models to FSA’s • Search • Comparing semantic data. • Converting query model to FSA, adding redundancy transitions. • Calculating Forward Simulation Relation (and cost) between the query FSA’s and target FSA’s. Technion – Israel Institute of Technology

  13. Calculating Semantic Similarity Foreach = SemanticSimilarity Where • SemanticSimilarity is: • Exact (1): if (nq) = (nm)or (nm) subclass of(nq) • Plug-in (0..1) - Weaker relation: if (nq)subclass of(nm) • Subsumes(0..1): (nm) is part of, or characterize, (nq) • Plug-in and Subsumes values are ‘soft’ values, derived from the length between (nq) and (nm). Technion – Israel Institute of Technology

  14. FSA Translation – An Example In the second stage, the query model and the target model are compiled into finite state-machines Technion – Israel Institute of Technology

  15. Constructing Query Model Redundancy • But, there are many ways to model something, even though we mean the same thing…    Original Acceptable Forms Technion – Israel Institute of Technology

  16. Query Model Redundancy – cont’d Redundant transitions are added to the query FSM: • A special utility cost function is attached to each extra transition, representing the amount in which taking the transition may harm the equivalence between the models. Technion – Israel Institute of Technology

  17. Matching by Simulating • The target model equivalence to the query model is calculated by reasoning on forward simulation relation between the models. • The relation simulates the notion that for each execution of the target model there is a corresponding execution of the query model. • In a formal manner, a forward simulation from automaton Tqto Tt is a relation f on SqStwith the following properties: • For each start state aIq there exists a start state bIt so that f(a, b) holds. • If aSq is a reachable state Tq and bStis a reachable state of Tt and f(a,b) holds and there exists an execution fragment  so that , there exists an execution path , so that , f(a’,b’) holds and  = . Technion – Israel Institute of Technology

  18. Evaluation • The efficiency of OPOSSUM will be tested using an experiment. • A benchmark of semantic web services in various fields (commerce, news, finance etc). • Measurement of: • Recall - proportion of relevant material actually retrieved • Precision - proportion of retrieved material actually relevant • The evaluation would be used to fine-tune the cost utility function. Technion – Israel Institute of Technology

  19. Summary and Contribution • General Community: • Prototype of a semantic matching engine for real life. • A taxonomy for model redundancy (can be used for UML and programming languages). • OPM Community: • Formal definition of the capabilities of an OPM model. • Matching algorithm for OPM models. • Research opportunities in Web services and Semantic Web. Technion – Israel Institute of Technology

  20. References [1] Dori, D., Toch, E., Reinhartz-Berger, I., Modeling Semantic Web Services with OPM/S – A Human and Machine-Interpretable Language, Third International Workshop on Web Dynamics, WWW 2004, New York, May 2004. [2] Sirin, E., Hendler, J., Parsia, B., Semi-automatic composition of web services using semantic descriptions. Web Services: Modeling, Architecture and Infrastructure workshop in conjunction with ICEIS2003, April 2003. [3] Xin Dong, Alon Y. Halevy, Jayant Madhavan, Ema Nemes, Jun Zhang: Simlarity Search for Web Services. VLDB 2004.(http://haydn.cs.washington.edu:8080/won/wonServlet) [4] http://www.alphaworks.ibm.com/tech/owsbi Technion – Israel Institute of Technology

  21. Thank you Technion – Israel Institute of Technology

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