Top-k retrieval for ontology mediated access to relational databases

We address the problem of evaluating ranked top-k queries in the context of ontology mediated access over relational databases. An ontology layer is used to define the relevant abstract concepts and relations of the application domain, while facts with associated score are stored into a relational database. Queries are conjunctive queries with ranking aggregates and scoring functions. The results of a query may be ranked according to the score and the problem is to find efficiently the top-k ranked query answers.

[1]  Umberto Straccia,et al.  Semantic-Based Top-k Retrieval for Competence Management , 2009, ISMIS.

[2]  Umberto Straccia,et al.  Top-k Retrieval for Automated Human Resource Management , 2009, SEBD.

[3]  Abraham Kandel,et al.  Implementing Imprecision in Information Systems , 1985, Inf. Sci..

[4]  Diego Calvanese,et al.  The Description Logic Handbook: Theory, Implementation, and Applications , 2003, Description Logic Handbook.

[5]  Diego Calvanese,et al.  Data Complexity of Query Answering in Description Logics , 2006, Description Logics.

[6]  Franz Baader,et al.  Pushing the EL Envelope , 2005, IJCAI.

[7]  Umberto Straccia,et al.  Query Answering in Normal Logic Programs Under Uncertainty , 2005, ECSQARU.

[8]  Jeffrey D. Ullman,et al.  Principles Of Database And Knowledge-Base Systems , 1979 .

[9]  Umberto Straccia SoftFacts: A top-k retrieval engine for ontology mediated access to relational databases , 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.

[10]  Jeff Z. Pan,et al.  Scalable querying services over fuzzy ontologies , 2008, WWW.

[11]  Umberto Straccia Uncertainty Management in Logic Programming: Simple and Effective Top-Down Query Answering , 2005, KES.

[12]  Umberto Straccia,et al.  Vague Knowledge Bases for Matchmaking in P2P E-Marketplaces , 2007, ESWC.

[13]  Jeffrey D. Ullman,et al.  Principles of Database and Knowledge-Base Systems, Volume II , 1988, Principles of computer science series.

[14]  Umberto Straccia,et al.  Fuzzy matchmaking in e-marketplaces of peer entities using Datalog , 2009, Fuzzy Sets Syst..

[15]  Umberto Straccia,et al.  Top-k Retrieval in Description Logic Programs Under Vagueness for the Semantic Web , 2007, SUM.

[16]  Diego Calvanese,et al.  Linking Data to Ontologies , 2008, J. Data Semant..

[17]  Ihab F. Ilyas,et al.  A survey of top-k query processing techniques in relational database systems , 2008, CSUR.

[18]  Umberto Straccia,et al.  Fuzzy Description Logic Programs , 2007 .

[19]  I. Horrocks,et al.  The Instance Store: DL Reasoning with Large Numbers of Individuals , 2004, Description Logics.

[20]  Umberto Straccia,et al.  Towards Top-k Query Answering in Description Logics: The Case of DL-Lite , 2006, JELIA.

[21]  Umberto Straccia,et al.  Towards Vague Query Answering in Logic Programming for Logic-Based Information Retrieval , 2007, IFSA.

[22]  Umberto Straccia An Ontology Mediated Multimedia Information Retrieval System , 2010, 2010 40th IEEE International Symposium on Multiple-Valued Logic.

[23]  Patrick Bosc,et al.  SQLf: a relational database language for fuzzy querying , 1995, IEEE Trans. Fuzzy Syst..

[24]  Umberto Straccia,et al.  Fuzzy Bilateral Matchmaking in e-Marketplaces , 2008, KES.

[25]  Moni Naor,et al.  Optimal aggregation algorithms for middleware , 2001, PODS.

[26]  B. C. Brookes,et al.  Information Sciences , 2020, Cognitive Skills You Need for the 21st Century.

[27]  Umberto Straccia,et al.  Managing Uncertainty and Vagueness in Description Logics, Logic Programs and Description Logic Programs , 2008, Reasoning Web.

[28]  Boris Motik,et al.  Tractable query answering and rewriting under description logic constraints , 2010, J. Appl. Log..

[29]  Claudio Gutierrez,et al.  Survey of graph database models , 2008, CSUR.

[30]  Umberto Straccia,et al.  Towards Top-k Query Answering in Deductive Databases , 2006, 2006 IEEE International Conference on Systems, Man and Cybernetics.

[31]  Diego Calvanese,et al.  Data Integration through DL-LiteA Ontologies , 2008, SDKB 2008.

[32]  Moshe Y. Vardi The complexity of relational query languages (Extended Abstract) , 1982, STOC '82.

[33]  Andrea Calì,et al.  Query rewriting and answering under constraints in data integration systems , 2003, IJCAI.

[34]  Peter Vojtás,et al.  Fuzzy logic aggregation for semantic web search for the best (top-k) answer , 2006, Fuzzy Logic and the Semantic Web.

[35]  Diego Calvanese,et al.  DL-Lite: Tractable Description Logics for Ontologies , 2005, AAAI.

[36]  Jeffrey D. Uuman Principles of database and knowledge- base systems , 1989 .

[37]  Umberto Straccia Answering Vague Queries in Fuzzy DL-Lite , 2006 .

[38]  Boris Motik,et al.  Data Complexity of Reasoning in Very Expressive Description Logics , 2005, IJCAI.

[39]  Domenico Fabio Savo,et al.  Filling the Gap between OWL 2 QL and QuOnto: ROWLKit , 2009, Description Logics.

[40]  Diego Calvanese,et al.  Data Integration throughDL-LiteA Ontologies , 2008, SDKB.