Query Expansion Methods and Performance Evaluation for Reusing Linking Open Data of the European Public Procurement Notices

The aim of this paper is to present some methods to expand user queries and a performance evaluation to retrieve public procurement notices in the e-Procurement sector using semantics and linking open data. Taking into account that public procurement notices contain information variables like type of contract, region, duration, total value, target enterprise, etc. different methods can be applied to expand user queries easing the access to the information and providing a more accurate information retrieval system. Nevertheless expanded user queries can involve an extra-time in the process of retrieving notices. That is why a performance evaluation is outlined to tune up the semantic methods and the generated queries providing a scalable and time-efficient system. On the other hand this system is based on the use of semantic web technologies so it is necessary to model the unstructured information included in public procurement notices (organizations, contracting authorities, contracts awarded, etc.), enrich that information with existing product classification systems and linked data vocabularies and publish the relevant data extracted out of the notices following the linking open data approach. In this new LOD realm these techniques are considered to provide added-value services like search, matchmaking geo-reasoning, or prediction, specially relevant to small and medium enterprises (SMEs).

[1]  Óscar Corcho,et al.  Semantics and Optimization of the SPARQL 1.1 Federation Extension , 2011, ESWC.

[2]  Roi Blanco,et al.  Caching search engine results over incremental indices , 2010, WWW '10.

[3]  Jörg Leukel,et al.  Exchange of Catalog Data in B2B Relationships - Analysis and Improvement , 2002, ICWI.

[4]  Jose Emilio Labra Gayo,et al.  Doing business by selling free services , 2009 .

[5]  Abraham Bernstein,et al.  OptARQ: A SPARQL Optimization Approach based on Triple Pattern Selectivity Estimation , 2007 .

[6]  Jeff Z. Pan,et al.  The Semanic Web: Research and Applications - 8th Extended Semantic Web Conference, ESWC 2011, Heraklion, Crete, Greece, May 29 - June 2, 2011, Proceedings, Part II , 2011, ESWC.

[7]  G. R. Amin,et al.  Document Similarity: A New Measure Using OWA , 2009, 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery.

[8]  Li Ma,et al.  Efficiently querying rdf data in triple stores , 2008, WWW.

[9]  José Emilio Labra Gayo,et al.  Searching over Public Administration Legal Documents Using Ontologies , 2006, JCKBSE.

[10]  Martin Hepp,et al.  Possible Ontologies: How Reality Constrains the Development of Relevant Ontologies , 2007, IEEE Internet Computing.

[11]  Rubén Posada-Gómez,et al.  HYDRA: A Middleware-Oriented Integrated Architecture for e-Procurement in Supply Chains , 2010, Trans. Comput. Collect. Intell..

[12]  Michael Schmidt,et al.  Foundations of SPARQL query optimization , 2008, ICDT '10.

[13]  Daniel Schwabe,et al.  A hybrid approach for searching in the semantic web , 2004, WWW '04.

[14]  Paul R. Cohen,et al.  Information retrieval by constrained spreading activation in semantic networks , 1987, Inf. Process. Manag..

[15]  Abdelghani Bellaachia,et al.  Enhanced Query Expansion in English-Arabic CLIR , 2008, 2008 19th International Workshop on Database and Expert Systems Applications.

[16]  Emilio Rubiera Azcona,et al.  Promoting Government Controlled Vocabularies for the Semantic Web : the EUROVOC Thesaurus and the CPV Product Classification System , 2008 .

[17]  Peter Mika,et al.  Ad-hoc object retrieval in the web of data , 2010, WWW '10.