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Semantic-based matchmaking and query refinement for B2C e-marketplaces

Semantic-based matchmaking and query refinement for B2C e-marketplaces. S. Colucci, T. Di Noia, E. Di Sciascio, A. Ragone , R. Rizzi Politecnico di Bari. F.M. Donini Università della Tuscia, Viterbo. B2C Scenario. Satellite TV system for football world championship. B (Business)

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Semantic-based matchmaking and query refinement for B2C e-marketplaces

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  1. Semantic-based matchmaking and query refinement for B2C e-marketplaces S. Colucci, T. Di Noia, E. Di Sciascio, A. Ragone, R. Rizzi Politecnico di Bari F.M. Donini Università della Tuscia, Viterbo Bari 26-27 giugno 2006

  2. B2C Scenario Satellite TV system for football world championship • B (Business) • Domain expertise • Technically advertised resources • Fix resources descriptions • C (Consumer) • Lack of knowledge domain • Lack of technical vocabulary • Vague buying ideas (shop assistant) NEED FOR A BRIDGE Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

  3. Challenge • Match resource to potential buyer’s interests (semantic annotation) • Facilitating exploration and selection of product characteristics (user friendly interaction) Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

  4. Outline • Application general features • Common sense user needs • System Description • Matchmaking Steps • Conclusions Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

  5. ApplicationFeatures • Benefit of semantic annotation: - richness of descriptions - reasoning services for matchmaking, ranking and explanation • User friendly interaction: - query formulation process - query language (expressiveness) Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

  6. User Needs • Support in the searching process: find the right product starting from a “vague idea” (incomplete information and preference elicitation) • Efficiency and trust: find the right product being confident the system finds the best one. • Ranking Criteria: price is not the only one criterion! • Friendliness: no technological gaps to overcome in order to use the system (no specific skill or learning effort) Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

  7. System Behavior(1/8) • MARKETPLACE SELECTION • Domain independence • On the fly ontology selection • On the fly marketplace creation Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

  8. System Behavior(2/8) • GUI : • Section (a)-(b)-(d): navigation panel • Section (c)-(e): query panel Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

  9. System Behavior(3/8) NAVIGATION PANEL: • Ontology browsing • Intensional navigation (top-down approach) • Most generic ontology classes shown in the top of (a) as entry points • Properties on which is possible to impose numeric restrictions shown in the bottom of (a) • Subclasses and roles of selected entry points shown in (b) • Navigation and zoom out by the history bar in (d) • Selected characteristics dragged in the query panel and added to the user final query Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

  10. System Behavior(4/8) • QUERY PANEL: • Positive preferences in (e) • Negative preferences in (c) • Preference removal by right clicking • Positive preferences all set strict in the initial query Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

  11. System Behavior(5/8) MATCHMAKING PROCESS EXECUTION: • Search for a match for the formulated query with all the semantic-enabled descriptions of supplies within the marketplace • Reasoning services for matchmaking and ranking provided by MaMaS: http://sisinflab.poliba.it/MAMAS-tng/ • Communication with MaMaS via DIG 1.1 interface over http Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

  12. System Behavior(6/8) • RESULTS WINDOW: • Section (a)-(b): LIST PANEL • Section (c)-(d): QUERY REFINEMENT PANEL Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

  13. System Behavior(7/8) • LIST PANEL: • Ranked list of appealing supplies within the marketplace • Logical Explanation on match results • Information for each retrieved item: • - Description: image, natural language description (transliteration of OWL description) • - Match value: semantic-based computed rank • - Match Explanation: fulfilled, unspecified, conflicting and additional characteristics w.r.t. the request • Multi-page visualization to be browsed by (b) Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

  14. System Behavior(8/8) • QUERY REFINEMENT PANEL: • Query visualized in (c) • Additional information (bonus) related to the offers currently displayed in the list panel shown in (d) • Possible query refinements: • - relaxing some characteristics setting them to negotiable (also supplies with features in conflict with the negotiable ones are considered) • - adding new characteristics from the bonus currently displayed in (d) • A NEW SEARCH CAN START! Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

  15. MATCHMAKING STEPS(1/2) 1. Formalization of the user request w.r.t. the ontology: all requested characteristics are set strict. 2. All the supplies in potential match are retrieved: fulfilled, uncertain and additional feature (Concept Abduction Problem). Computation of a semantic-based match value 3. Ranking of all the retrieved supplies w.r.t. their semantic-based match value. All the additional features displayed in the bottom side of the query refinement panel. Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

  16. MATCHMAKING STEPS(2/2) 4. Possible query refinement by the user. 5. New retrieved process performed: computation of a semantic-based match value based on fulfilled, unspecified, conflicting and additional characteristics. Contract Abduce Partial Potential Full Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

  17. Conclusions • System showing benefits of semantic markup of descriptions in an e-marketplace • System satisfying common sense user needs: support in the searching process, efficiency and trust and ranking criteria Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

  18. Future Work • System is being tested by human volunteers for evaluating both the degree of correspondence of the approach to commonsense judgment and the usability of the tool • Ajax-based GUI • Good qualities ontology modeling • Evaluation of different match degree functions, with extra-ontological information, under investigation Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

  19. Special Thanks Marketplace application originally designed and developed by Raffaele Rizzi Re-engineered and maintained by Francesco Di Cugno http://sisinflab.poliba.it/marketplace/ Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

  20. Thank you Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

  21. Query process Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

  22. Conclusions • System showing benefits of semantic markup ofdescriptions in an e-marketplace • System satisfying common sense user needs: support in the searching process, efficiency and trust and ranking criteria • System tested by human volunteers for evaluating both the theoretical approach and the usability of the tool • Evaluation of different match degree functions, with extra-ontological information, under investigation Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

  23. Semantic Annotation • Resources formalized in ALN Description Logic(DL): - unambiguous shared meaning of terms - Open World Assumption(OWA) for descriptions • Semantic-based Matchmaking - Subsumption for Potential Match - Contraction for belief revision PARTIAL POTENTIAL - Abduction for explanation POTENTIAL FULL • Logic-based Ranking of resources Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

  24. Query process • Fully supported searching process - hidden product technicalities - visual representation of user needs - ongoing specification of buying ideas - searched product features revision - additional features suggested - logic-based overall ranking vs feature-specific ranking Convegno Italiano di Logica Computazionale. Bari, 26-27 Giugno 2006

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