A semantic-based fully visual application for matchmaking and query refinement in B2C e-marketplaces

This paper presents a visual application in the framework of semantic-enabled e-marketplaces aimed at fully exploiting semantics of supply/demand descriptions in B2C and C2C e-marketplaces. Distinguishing aspects of the framework include logic-based explanation of request results, semantic ranking of matchmaking results, logic-based request refinement. The visual user interface has been designed and implemented to be immediate and simple, and it requires no knowledge of any logic principle to be fully used.

[1]  Francesco M. Donini,et al.  Knowledge elicitation for query refinement in a semantic-enabled e-marketplace , 2005, ICEC '05.

[2]  Takahiro Kawamura,et al.  Semantic Matching of Web Services Capabilities , 2002, SEMWEB.

[3]  Zdenek Zdráhal,et al.  Story fountain: intelligent support for story research and exploration , 2004, IUI '04.

[4]  Henry Lieberman,et al.  Intelligent profiling by example , 2001, IUI '01.

[5]  Abraham Bernstein,et al.  Querying Ontologies: A Controlled English Interface for End-Users , 2005, SEMWEB.

[6]  Tiziana Catarci,et al.  An Ontology Based Visual Tool for Query Formulation Support , 2004, OTM Workshops.

[7]  Hideo Shimazu,et al.  ExpertClerk: A Conversational Case-Based Reasoning Tool forDeveloping Salesclerk Agents in E-Commerce Webshops , 2002, Artificial Intelligence Review.

[8]  Francesco M. Donini,et al.  A System for Principled Matchmaking in an Electronic Marketplace , 2004, Int. J. Electron. Commer..

[9]  Robin Burke,et al.  Knowledge-based recommender systems , 2000 .

[10]  Francesco M. Donini,et al.  A system for principled matchmaking in an electronic marketplace , 2003, WWW '03.

[11]  Robin D. Burke,et al.  The Wasabi Personal Shopper: A Case-Based Recommender System , 1999, AAAI/IAAI.

[12]  Ian Horrocks,et al.  A software framework for matchmaking based on semantic web technology , 2003, WWW '03.

[13]  M. E. Maron,et al.  An evaluation of retrieval effectiveness for a full-text document-retrieval system , 1985, CACM.

[14]  Diego Calvanese,et al.  The Description Logic Handbook , 2007 .

[15]  Tiziana Catarci,et al.  Visual Query Systems for Databases: A Survey , 1997, J. Vis. Lang. Comput..

[16]  Boi Faltings,et al.  SmartClients: Constraint Satisfaction as a Paradigm for Scaleable Intelligent Information Systems , 2004, Constraints.

[17]  Francesco M. Donini,et al.  Concept abduction and contraction for semantic-based discovery of matches and negotiation spaces in an e-marketplace , 2004, ICEC '04.

[18]  Ramanathan V. Guha,et al.  Semantic search , 2003, WWW '03.

[19]  Zdenek Zdráhal,et al.  Semantic Browsing of Digital Collections , 2005, International Semantic Web Conference.

[20]  Kristian J. Hammond,et al.  The FindMe Approach to Assisted Browsing , 1997, IEEE Expert.

[21]  Francesco M. Donini,et al.  A Uniform Tableaux-Based Method for Concept Abduction and Contraction in Description Logics , 2004, ECAI.

[22]  Diego Calvanese,et al.  Dwq : Esprit Long Term Research Project, No 22469 on the Decidability of Query Containment under Constraints on the Decidability of Query Containment under Constraints , 2022 .

[23]  Jérôme Euzenat,et al.  A Survey of Schema-Based Matching Approaches , 2005, J. Data Semant..

[24]  Greg Linden,et al.  Interactive Assessment of User Preference Models: The Automated Travel Assistant , 1997 .

[25]  Giovanni Maria Sacco,et al.  The intelligent e-store: easy interactive product selection and comparison , 2005, Seventh IEEE International Conference on E-Commerce Technology (CEC'05).

[26]  Pratyush Kumar,et al.  Evaluating example-based search tools , 2004, EC '04.

[27]  Ian Horrocks,et al.  OWL: A Description Logic Based Ontology Language , 2005, ICLP.