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Semantic Search based on Ontology Alignment for Information Retrieval
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 107 - Number 10 |
| Year of Publication: 2014 |
| Authors: Manju Mony, Jyothi M. Rao, Manish M. Potey |
10.5120/18789-0125
|
Manju Mony, Jyothi M. Rao, Manish M. Potey . Semantic Search based on Ontology Alignment for Information Retrieval. International Journal of Computer Applications. 107, 10 ( December 2014), 25-33. DOI=10.5120/18789-0125
Abstract
Traditional search is keyword based search and does not focus on relationship between the words. In semantic search, the search is performed on basis of the meaning of the terms and concepts. The semantics i. e. meaning is expressed through structured knowledge representation or Ontologies. Resource Description Framework (RDF) is used as the data model and SPARQL query language is used to query the RDF data. Currently, there is lot of RDF based data set, e. g. Dbpedia, Freebase, Geonames etc. Semantic search is gaining popularity in recent times. As systems cannot exist in isolation but need to interact with each other, complex systems may require integration of multiple systems. Semantic search systems may take input from heterogeneous systems, in which case, the common and shared entities have to be identified and mapped properly. Also, in semantic search, user has to enter query in formal query language SPARQL, which is quite difficult to learn and use for laymen. We are presenting herewith, an application in which we have constructed multiple ontologies that are inherently unique but are related to each other. The system performs ontology alignment to allow for inter-operation between them. Also, it provides a natural language query (NLQ) interface. It converts the Natural Language (NL) input to SPARQL query. It answers queries across these multiple ontologies and abstracts them as a single linked unit. Currently, it is working for simple as well as some type of complex queries.
References
- Tim Berners-Lee, James, The Semantic Web, Scientific American, May 2001, vol. 284, no. 5, pp 34-43.
- D. Brickley and R. V. Guha (Eds), RDF Vocabulary Description Language 1. 0: RDF Schema, W3C Recommendation, 10 February 2004. Available at http://www. w3. org/TR/rdf-schema/
- Khadija Elbedweihy, Stuart N. Wrigley, and Fabio Ciravegna. 2012. Evaluating semantic search query approaches with expert and casual users. In Proceedings of the 11th international conference on The Semantic Web - Volume Part II (ISWC'12), Springer-Verlag, Berlin, Heidelberg, 274-286
- Kaufmann, E. , Bernstein, A. , Fischer, L. : NLP-Reduce: A naive but domain independent natural language interface for querying ontologies. In: Franconi, E. , Kifer, M. , May, W. (eds. ) ESWC 2007. LNCS, vol. 4519, Springer, Heidelberg (2007)
- D. Damljanovic. M. Agatonovic. and H. Cunningham. "FREyA : An Interactive Way of Querying Linked Data Using Natural Language, " in Proceedings of the 8th international conference on The Semantic Web. 2011. pp. 125-138.
- Lehmann, J. , Buhmann, L. : Autosparql: Let users query your knowledge base. In:Proceedings of the 8th Extended Semantic Web Conference on The Semantic Web:Research and Applications - Volume Part I. pp. 63{79. ESWC'11, Springer-Verlag,Berlin, Heidelberg (2011)
- Fernandez, M. , Cantador, I. , Lopez, V. , Vallet, D. , Castells, P. , Motta, E. . Semantically enhanced Information Retrieval: an ontology-based approach. Web Semantics: Science, Services and Agents on the World Wide Web, North America, 9, jan. 2012.
- Chauhan, R. ; Goudar, R. ; Sharma, R. ; Chauhan, A. , "Domain ontology based semantic search for efficient information retrieval through automatic query expansion," Intelligent Systems and Signal Processing (ISSP), 2013 International Conference on , vol. , no. , pp. 397,402, 1-2 March 2013
- Chunfei Zhang, Zhiyi Fang, A New Electronic Medical Record Retrieval System Based on Ontology and Mapping Algorithm, Journal of Information & Computational Science 10:14, 4603-4610, 2013
- Swaran Lata, Bhaskar Sinha, Ela Kumar, Somnath Chandra, Raghu Arora, Semantic Web Query on e-Governance Data and Designing Ontology for Agriculture Domain, International Journal of Web & Semantic Technology (IJWesT) , 04(03), 65 – 72, 2013
- R. Suganyakala & Dr. R. R. Rajalaxmi , "Movie Related Information Retrieval Using Ontology Based Semantic Search", International Conference on Information Communication and Embedded Systems (ICICES), 2013
- Protege Overview, http://protege. stanford. edu/overview/
- The Alignment API, http://alignapi. gforge. inria. fr
- Open Refine, http://openrefine. org
- Marklogic, http://www. marklogic. com
- The Stanford Parser: A statistical parser, http://nlp. stanford. edu/software/lex-parser. shtml
- Marie-Catherine de Marneffe, Christopher D. Manning, "The Stanford typed dependencies manual" in Revised for Stanford Parser v1. 6. 2, February, 2010.
- Oegov ontologies for e-government, http://oegov. org
- IIB, https://iib. gov. in
- Maria Keet C. , Aspects of Ontology Integration, 2004
- Studer R, Benjamins VR, Fensel D, Knowledge Engineering: Principles and Methods, IEEE Transactions on Data and Knowledge Engineering, 25(1-2), pp. 161-197, 1998.
- P Hitzler, M Krotzsch, S Rudolph, Foundations of semantic web technologies, Chapman and Hall/CRC, 2010
- John Hebeler, Matthew Fisher, Ryan Blace, Andrew Perez-Lopez, and Mike Dean, Semantic Web Programming, John Wiley & Sons Inc. , Chichester, West Sussex, Hoboken, NJ, (2009).
- Dr. Harald Sack, Feb 2013, Semantic Web Technologies Course, Courses – Open HPI, Retrieved from https://openhpi. de/course/semanticweb
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