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OPOSSUM: Object-PrOcess Structural / Semantic Unified Matching

This workshop presentation focuses on OPOSSUM, a search engine designed to improve searching and matching in semantic web services (SWS) using Object-Process Methodology (OPM/S). It highlights motivation, challenges, and evaluations associated with matching services across varying abstraction levels and partial results. The OPOSSUM mechanism employs pre-indexing and finite state automata (FSA) to calculate capability equivalence between query and target models. The results aim to enhance semantic service retrieval efficiency and accuracy, fostering better integration of diverse web services.

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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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