Exploiting Metrics for Semantic Web Service Discovery

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Exploiting Metrics for Semantic Web Service Discovery

  1. 1. Exploiting Metrics for Semantic Web Service Discovery - IEEE ICWS’09, Los Angeles, CA, USA, July 08, 2009 - Stefan Dietze , Alessio Gugliotta, John Domingue Knowledge Media Institute, The Open University, UK
  2. 2. <ul><li>Semantic Web Services (SWS) mediation </li></ul><ul><li>Two-fold representation approach for SWS </li></ul><ul><li>Prototypical application </li></ul><ul><li>Conclusions </li></ul>Outline
  3. 3. Introduction Semantic Web Services <ul><ul><li>Formal specifications of Web services in terms of their capabilities (Cap) , interfaces (If) and non-functional properties (Nfp) </li></ul></ul><ul><ul><li>Capabilities describe assumptions (Ass) and effects (Eff) </li></ul></ul><ul><ul><li>Defined through ontologies O, i.e. as tuple of concepts C , instances I , properties P , relations R and axioms A </li></ul></ul><ul><ul><li>Reference models such as OWL-S, WSMO, SAWSDL </li></ul></ul>sws:WebService SWS.2 sws:WebService SWS.3 sws:WebService SWS.1 WebService WS.2 WebService WS.3 WebService WS.1
  4. 4. <ul><li>SWS discovery: matchmaking of capabilities of SWS e.g. : </li></ul><ul><li>SWS brokers match logical expressions (e.g. & ) </li></ul>Introduction Semantic Mediation for SWS Discovery sws:WebService SWS.2 sws:WebService SWS.3 sws:Request R.1 sws:WebService SWS.1 WebService WS.2 WebService WS.3 WebService WS.1 ? ?
  5. 5. <ul><li>SWS discovery: matchmaking of capabilities of SWS e.g. : </li></ul><ul><li>SWS brokers match logical expressions (e.g. & ) </li></ul><ul><li>Heterogeneous SWS annotations </li></ul><ul><li>Semantic mediation: alignment/mapping of SWS concepts/instances across distinct SWS </li></ul>Introduction Semantic Mediation for SWS Discovery sws:WebService SWS.2 sws:WebService SWS.3 sws:Request R.1 sws:WebService SWS.1 WebService WS.2 WebService WS.3 WebService WS.1 Semantic-Level Mediation Mediation between different semantic representations
  6. 6. Semantic Mediation Issues SWS 1 (get-flowers) <Color rdf:ID=&quot;Lilac&quot;/> <Location rdf:ID=&quot;Milton_Keynes&quot;/> has-assumption SWS Request (Consumer)
  7. 7. Semantic Mediation Issues SWS 1 (get-flowers) <Color rdf:ID=&quot;Lilac&quot;/> <Location rdf:ID=&quot;Milton_Keynes&quot;/> SWS 2 (provide-flowers) <Colour rdf:ID=&quot;Purple&quot;/> <geospatialLocation rdf:ID=&quot;M-K&quot;/> has-assumption has-assumption SWS (Provider) SWS Request (Consumer)
  8. 8. Semantic Mediation Issues SWS 1 (get-flowers) <Color rdf:ID=&quot;Lilac&quot;/> <Location rdf:ID=&quot;Milton_Keynes&quot;/> SWS 2 (provide-flowers) <Colour rdf:ID=&quot;Purple&quot;/> <geospatialLocation rdf:ID=&quot;M-K&quot;/> has-assumption has-assumption ? SWS (Provider) SWS Request (Consumer)
  9. 9. <ul><li>Issues: </li></ul><ul><ul><li>Heterogeneous SWS annotations </li></ul></ul><ul><ul><li>Lack of implicit similarity information (symbol grounding problem) </li></ul></ul><ul><ul><li>Reliance on either: </li></ul></ul><ul><ul><ul><li>(i) manual mapping rules </li></ul></ul></ul><ul><ul><ul><li>(ii) ontology mapping mechanisms (exploiting linguistic or structural similarities) </li></ul></ul></ul><ul><ul><li>Costly and error-prone </li></ul></ul><ul><ul><li>=> representations which implicitly represent similarities across heterogeneous SWS ? </li></ul></ul>Semantic Mediation Issues
  10. 10. <ul><ul><li>Refining SWS ontologies through multiple Conceptual Spaces (CS), i.e. multidimensional, geometrical vector spaces </li></ul></ul><ul><ul><li>Concept C in one SWS ontology O => Conceptual Space CS </li></ul></ul><ul><ul><li>Instance I of C => member M (vector) in CS </li></ul></ul>Two-fold Approach Refining SWS through Conceptual Spaces
  11. 11. <ul><ul><li>Similarity-computation between SWS instances by means of spatial distances in CS </li></ul></ul><ul><ul><li>Common agreement at schema (i.e. CS) level </li></ul></ul><ul><ul><li>Facilitated through wide-spread use of upper-level ontologies (DOLCE, SUMO…) </li></ul></ul>Two-fold Approach Refining SWS through Conceptual Spaces
  12. 12. <ul><li>CS ontology enabling to represent SWS concepts / instances through CS: </li></ul><ul><ul><li>CS (refining concept C ) represented through set of dimensions d i each associated with a prominence value p i : , </li></ul></ul><ul><ul><li>Assignment of measurement scales </li></ul></ul><ul><ul><li>Dimension d j might be refined by further dimensions: (CS possibly composed of subspaces), </li></ul></ul>Two-fold Approach Formal CS Ontology
  13. 13. <ul><li>CS ontology enabling to represent SWS concepts / instances through CS: </li></ul><ul><ul><li>CS (refining concept C ) represented through set of dimensions d i each associated with a prominence value p i : , </li></ul></ul><ul><ul><li>Assignment of measurement scales </li></ul></ul><ul><ul><li>Dimension d j might be refined by further dimensions: (CS possibly composed of subspaces), </li></ul></ul><ul><ul><li>Members M (refining instances I ) represented through vectors in CS: </li></ul></ul><ul><ul><li>Similarity between two SWS instances (members) V and U calculated by means of their Euclidean distance: ( where is the mean of a dataset U and s u is the standard deviation from U) </li></ul></ul>Two-fold Approach Formal CS Ontology
  14. 14. A Similarity-based Mediator Implementation based on WSMO <ul><li>Implementation based on Web Service Modelling Ontology (WSMO) and SWS reasoning environment IRS-III for similarity-based SWS discovery </li></ul>
  15. 15. A Similarity-based Mediator Implementation based on WSMO <ul><li>Implementation based on Web Service Modelling Ontology (WSMO) and SWS reasoning environment IRS-III for similarity-based SWS discovery </li></ul><ul><li>WSMO Mediator: computation of similarities between given request (WSMO Goal, G 1 ) and set of x associated SWS ( SWS 1 ..SWS x ) </li></ul><ul><li>Implemented through mediation Web service </li></ul>
  16. 16. <ul><li>MedWS SWS 1.1 computes x similarity values with Sim(G 1 ,SWS j ) defined as reciprocal to the mean value of their individual member distances: </li></ul><ul><li>With dist k being the distance between one particular member v i of G 1 and one member of SWS j in the same CS </li></ul>Measurement-based Service Selection Implementation based on WSMO
  17. 17. <ul><li>Uses representational approach based on CS and similarity-based WSMO Mediator </li></ul><ul><li>Aims at retrieval of distributed video resources (provided within EU FP7 IP NoTube - http://notube.tv) </li></ul><ul><li>Keyword-based searches across 5 (REST) Web services built on top of the following (logical/physical) repositories </li></ul><ul><ul><li>BBC Backstage (world news feed) [ http://backstage.bbc.co.uk/ ] </li></ul></ul><ul><ul><li>Open Video [ http://www.open-video.org/ ] </li></ul></ul><ul><ul><li>YouTube (entertainment feed) [ http://www.youtube.com ] </li></ul></ul><ul><ul><li>OU channel on YouTube [ http://www.youtube.com/ou ] </li></ul></ul><ul><ul><li>YouTube (mobile feed) [ http://www.youtube.com/ou ] </li></ul></ul><ul><li>Similarity-based service discovery for a given request </li></ul>SWS Mediation based on CS Prototypical Application
  18. 18. SWS Mediation based on CS Prototypical Application SWS 1 : OU-youtube O 1 :Purp O 1 :Env SWS 2 : entertain-youtube O 2 :Purp O 2 :Env SWS 3 : open-video O 3 :Purp O 3 :Env SWS 4 : bbc-backstage O 4 :Purp O 4 :Env M 6 2 ={v 1 , v 2 } SWS 5 : mobile-youtube O 5 :Purp O 5 :Env CS 2 Environment Space CS 1 Purpose Space SWS 6 : get-video-request M 6 1 ={v 1, v 2 , v 3 } WS 1 : OU-youtube WS 2 : entertain-youtube WS 3 : open-video WS 4 : bbc-backstage WS 5 : mobile-youtube
  19. 19. SWS Mediation based on CS Prototypical Application SWS 1 : OU-youtube O 1 :Purp O 1 :Env SWS 2 : entertain-youtube O 2 :Purp O 2 :Env SWS 3 : open-video O 3 :Purp O 3 :Env SWS 4 : bbc-backstage O 4 :Purp O 4 :Env M 6 2 ={v 1 , v 2 } SWS 5 : mobile-youtube O 5 :Purp O 5 :Env CS 2 Environment Space CS 1 Purpose Space SWS 6 : get-video-request M 6 1 ={v 1, v 2 , v 3 } WS 1 : OU-youtube WS 2 : entertain-youtube WS 3 : open-video WS 4 : bbc-backstage WS 5 : mobile-youtube
  20. 20. SWS Mediation based on CS Prototypical Application SWS 1 : OU-youtube O 1 :Purp O 1 :Env SWS 2 : entertain-youtube O 2 :Purp O 2 :Env SWS 3 : open-video O 3 :Purp O 3 :Env SWS 4 : bbc-backstage O 4 :Purp O 4 :Env M 6 2 ={v 1 , v 2 } SWS 5 : mobile-youtube O 5 :Purp O 5 :Env CS 2 Environment Space CS 1 Purpose Space SWS 6 : get-video-request M 6 1 ={v 1, v 2 , v 3 } WS 1 : OU-youtube WS 2 : entertain-youtube WS 3 : open-video WS 4 : bbc-backstage WS 5 : mobile-youtube {(p 1 *information, p 2 *education, p 3 *leisure)} = CS 1 {(p 4 *resolution, p 5 *bandwidth)} = CS 2
  21. 21. SWS Mediation based on CS Prototypical Application <ul><li>SWS annotated with Assumption Ass defined through conjunction of instances (more expressive logical expressions to be considered) </li></ul><ul><li>Instances refined through vectors (members) </li></ul>
  22. 22. SWS Mediation based on CS Prototypical Application <ul><li>SWS annotated with Assumption Ass defined through conjunction of instances (more expressive logical expressions to be considered) </li></ul><ul><li>Instances refined through vectors (members) </li></ul>OU@Youtube SWS Educational purpose High resolution and bandwidth
  23. 23. SWS Mediation based on CS Prototypical Application SWS 1 : OU-youtube O 1 :Purp O 1 :Env SWS 2 : entertain-youtube O 2 :Purp O 2 :Env SWS 3 : open-video O 3 :Purp O 3 :Env SWS 4 : bbc-backstage O 4 :Purp O 4 :Env M 6 2 ={v 1 , v 2 } SWS 5 : mobile-youtube O 5 :Purp O 5 :Env CS 2 Environment Space CS 1 Purpose Space SWS 6 : get-video-request M 6 1 ={v 1, v 2 , v 3 } WS 1 : OU-youtube WS 2 : entertain-youtube WS 3 : open-video WS 4 : bbc-backstage WS 5 : mobile-youtube <ul><li>Requests (WSMO Goals) defined through AJAX-based UI </li></ul><ul><li>Requests consists of: </li></ul><ul><ul><li>Input parameters: set of keywords (free text) </li></ul></ul><ul><ul><li>Assumption: defined through vectors (measurements describing purpose and environment) </li></ul></ul><ul><li>Similarity-based discovery of most suitable service based on WSMO mediator </li></ul>
  24. 24. DEMO SWS 1 : OU-youtube O 1 :Purp O 1 :Env SWS 2 : entertain-youtube O 2 :Purp O 2 :Env SWS 3 : open-video O 3 :Purp O 3 :Env SWS 4 : bbc-backstage O 4 :Purp O 4 :Env M 6 2 ={v 1 , v 2 } SWS 5 : mobile-youtube O 5 :Purp O 5 :Env CS 2 Environment Space CS 1 Purpose Space SWS 6 : get-video-request M 6 1 ={v 1, v 2 , v 3 } WS 1 : OU-youtube WS 2 : entertain-youtube WS 3 : open-video WS 4 : bbc-backstage WS 5 : mobile-youtube
  25. 25. <ul><li>Some issues: </li></ul><ul><ul><li>SWS assumptions defined as conjunction of instances => consideration of arbitrary logical expressions required </li></ul></ul><ul><ul><li>Additional representational effort </li></ul></ul><ul><ul><li>Similarity-calculation requires overlapping CS and measurable quality dimensions </li></ul></ul>Conclusions Discussion and Summary
  26. 26. <ul><li>Some issues: </li></ul><ul><ul><li>SWS assumptions defined as conjunction of instances => consideration of arbitrary logical expressions required </li></ul></ul><ul><ul><li>Additional representational effort </li></ul></ul><ul><ul><li>Similarity-calculation requires overlapping CS and measurable quality dimensions </li></ul></ul><ul><li>… , however: </li></ul><ul><ul><li>Allows to compute similarities between distinct SWS </li></ul></ul><ul><ul><li>Reduces the required level of common ontological agreement (only required at schema level). </li></ul></ul>Conclusions Discussion and Summary
  27. 27. Thank you! <ul><li>E-mail: [email_address] </li></ul><ul><li>Web: http://people.kmi.open.ac.uk/dietze </li></ul>

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