ABSTRACT
Retrieval of domain-specific documents became attractive for the Semantic Web community due to the possibility of integrating classic Information Retrieval (IR) techniques with semantic knowledge. Unfortunately, the gap between the construction of a full semantic search engine and the possibility of exploiting a repository of ontologies covering all possible domains is far from being filled. Recent solutions focused on the aggregation of different domain-specific repositories managed by third-parties. In this paper, we present a semantic federated search engine developed in the context of the EEXCESS EU project. Through the developed platform, users are able to perform federated queries over repositories in a transparent way, i.e. without knowing how their original queries are transformed before being actually submitted. The platform implements a facility for plugging new repositories and for creating, with the support of general purpose knowledge bases, knowledge graphs describing the content of each connected repository. Such knowledge graphs are then exploited for enriching queries performed by users.
- F. Corcoglioniti, M. Dragoni, M. Rospocher, and A. P. Aprosio. Knowledge extraction for information retrieval. In The Semantic Web. Latest Advances and New Domains - 13th European Semantic Web Conference, ESWC 2016, Creete, Grecia, May 29 -- June 2, 2016. Proceedings. To appear., 2016. Google ScholarDigital Library
- C. da Costa Pereira, M. Dragoni, and G. Pasi. Multidimensional relevance: Prioritized aggregation in a personalized information retrieval setting. Information processing & management, 48(2):340--357, 2012. Google ScholarDigital Library
- C. Dwork, R. Kumar, M. Naor, and D. Sivakumar. Rank aggregation methods for the Web. Proceedings of the 10th international conference on World Wide Web, pages 613--622, 2001. Google ScholarDigital Library
- M. Hagen, M. Potthast, A. Beyer, and B. Stein. Towards optimum query segmentation: In doubt without. In Proceedings of the 21st ACM International Conference on Information and Knowledge Management, CIKM '12, pages 1015--1024, New York, NY, USA, 2012. ACM. Google ScholarDigital Library
- P. Ingwersen and K. Järvelin. The Turn - Integration of Information Seeking and Retrieval in Context, volume 18 of The Information Retrieval Series. Springer, 2005. Google ScholarDigital Library
- A. Kopliku, K. Pinel-Sauvagnat, and M. Boughanem. Aggregated search: A new information retrieval paradigm. ACM Computing Surveys (CSUR), 46(3):41, 2014. Google ScholarDigital Library
- J. Lu and J. Callan. Federated search of text-based digital libraries in hierarchical peer-to-peer networks. In Advances in Information Retrieval, pages 52--66. Springer, 2005. Google ScholarDigital Library
- G. Marchionini and R. White. Find what you need, understand what you find. Int. J. Hum. Comput. Interaction, 23(3):205--237, 2007. Google ScholarCross Ref
- D. Minnie and S. Srinivasan. Meta search engines for information retrieval on multiple domains. In Proceedings of the International Joint Journal Conference on Engineering and Technology (IJJCET 2011), pages 115--118. Citeseer, 2011.Google Scholar
- J. Montgomery, L. Si, J. Callan, and D. A. Evans. Effect of varying number of documents in blind feedback: analysis of the 2003 nrrc ria workshop bf_numdocs experiment suite. In Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval, pages 476--477. ACM, 2004. Google ScholarDigital Library
- X. Rong. word2vec parameter learning explained. CoRR, abs/1411.2738, 2014.Google Scholar
- M. Shokouhi and L. Si. Federated search. Foundations and Trends in Information Retrieval, 5(1):1--102, 2011. Google ScholarDigital Library
- N. Stojanovic. An approach for the efficient retrieval in ontology-enhanced information portals. In D. Karagiannis and U. Reimer, editors, Practical Aspects of Knowledge Management, 5th International Conference, PAKM 2004, Vienna, Austria, December 2--3, 2004, Proceedings, volume 3336 of Lecture Notes in Computer Science, pages 414--424. Springer, 2004. Google ScholarCross Ref
- S. Zwicklbauer, C. Seifert, and M. Granitzer. From general to specialized domain: Analyzing three crucial problems of biomedical entity disambiguation. In Q. Chen, A. Hameurlain, F. Toumani, R. Wagner, and H. Decker, editors, Database and Expert Systems Applications - 26th International Conference, DEXA 2015, Valencia, Spain, September 1--4, 2015, Proceedings, Part I, volume 9261 of Lecture Notes in Computer Science, pages 76--93. Springer, 2015. Google ScholarDigital Library
Index Terms
- A semantic federated search engine for domain-specific document retrieval
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