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Como trabalho futuro, desejamos expandir o conjunto de consultas que possam ser respondidas pela nossa técnica, suportando operações como negação e agregação. Além disso, utilizarmos estratégias de ranqueamento sobre o esquema como proposta em (LEAL et al., 2018) a fim de melhorar a eficiência da etapa de keyword matching

REFERÊNCIAS

ARNAOUT, H.; ELBASSUONI, S. Effective searching of rdf knowledge graphs. Journal of Web Semantics, v. 48, p. 66 – 84, 2018. ISSN 1570-8268.

AUER, S.; BIZER, C.; KOBILAROV, G.; LEHMANN, J.; CYGANIAK, R.; IVES, Z. Dbpedia: A nucleus for a web of open data. In: The semantic web. [S. l.]: Springer, 2007. p. 722–735. BARRÓN-CEDENO, A.; ROSSO, P.; AGIRRE, E.; LABAKA, G. Plagiarism detection across distant language pairs. In: ASSOCIATION FOR COMPUTATIONAL LINGUISTICS. Proceedings of the 23rd COLING. [S. l.], 2010. p. 37–45.

BAST, H.; BUCHHOLD, B.; HAUSSMANN, E. et al. Semantic search on text and knowledge bases. Foundations and Trends in Information Retrieval, Now Publishers, Inc., v. 10,R n. 2-3, p. 119–271, 2016.

BERNERS-LEE, T. Linked data, 2006. 2006.

BONDY, J. A.; MURTY, U. S. R. GRAPH THEORY WITH APPLICATIONS. [S. l.: s. n.], 1982.

CALVANESE, D.; COGREL, B.; KOMLA-EBRI, S.; KONTCHAKOV, R.; LANTI, D.; REZK, M.; RODRIGUEZ-MURO, M.; XIAO, G. Ontop: Answering sparql queries over relational databases. Semantic Web, IOS Press, v. 8, n. 3, p. 471–487, 2017.

CHANIAL, C.; DZIRI, R.; GALHARDAS, H.; LEBLAY, J.; CHANIAL, C.; DZIRI, R.; GALHARDAS, H.; LEBLAY, J.; NGUYEN, M.-h. L.; CHANIAL, C.; GALHARDAS, H. ConnectionLens : Finding Connections Across Heterogeneous Data Sources To cite this version : HAL Id : hal-01841009 ConnectionLens : Finding Connections Across Heterogeneous Data Sources. 2018.

CONSORTIUM, W. W. W. et al. Rdf 1.1 concepts and abstract syntax. World Wide Web Consortium, 2014.

CORMEN, T. H.; LEISERSON, C. E.; RIVEST, R. L.; STEIN, C. Introduction to algorithms. [S. l.]: MIT press, 2009.

DIJKSTRA, E. W. A note on two problems in connexion with graphs. Numerische mathematik, Springer, v. 1, n. 1, p. 269–271, 1959.

DUBEY, M.; DASGUPTA, S.; SHARMA, A.; HÖFFNER, K.; LEHMANN, J. Asknow. Eswc, n. c, 2016.

FENSEL, D. Ontologies. In: Ontologies. [S. l.]: Springer, 2001. p. 11–18.

GOMAA, W. H.; FAHMY, A. A. A survey of text similarity approaches. IJCA, Citeseer, v. 68, n. 13, p. 13–18, 2013.

HARA, C. S.; PORTO, F.; OGASAWARA, E. Tópicos em gerenciamento de dados e informações 2015. 2015.

HEATH, T.; BIZER, C. Linked data: Evolving the web into a global data space. Synthesis lectures on the semantic web: theory and technology, Morgan & Claypool Publishers, v. 1, n. 1, p. 1–136, 2011.

HWANG, F.; WINTER, P.; RICHARDS, D. The steiner tree problem. North-Holland, 1992. IZQUIERDO, Y. T.; GARCÍA, G. M.; MENENDEZ, E. S.; CASANOVA, M. A.; DARTAYRE, F.; LEVY, C. H. Quiow: a keyword-based query processing tool for rdf datasets and relational databases. In: SPRINGER. International Conference on Database and Expert Systems Applications. [S. l.], 2018. p. 259–269.

JACCARD, P. Étude comparative de la distribution florale dans une portion des alpes et des jura. Bull Soc Vaudoise Sci Nat, v. 37, p. 547–579, 1901.

JURAFSKY, D.; MARTIN, J. Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition. [S. l.: s. n.], 2008. v. 2.

KHAN, W.; DAUD, A.; NASIR, J. A.; AMJAD, T. A survey on the state-of-the-art machine learning models in the context of nlp. Kuwait journal of Science, v. 43, n. 4, 2016.

KOMPELLA, V. P.; PASQUALE, J. C.; POLYZOS, G. C. Multicast routing for multimedia communication. IEEE/ACM Transactions on Networking (TON), IEEE Press, v. 1, n. 3, p. 286–292, 1993.

LEAL, V. V. B.; MACÊDO, J. A. F. de; PERES, L.; ARAÚJO, D. Pytology: rumo ao cálculo de relevância sobre dados rdf. In: SBBD. [S. l.: s. n.], 2018. p. 229–234.

LOPEZ, V.; PASIN, M.; MOTTA, E. Aqualog: An ontology-portable question answering system for the semantic web. In: SPRINGER. European Semantic Web Conference. [S. l.], 2005. p. 546–562.

LOPEZ, V.; UREN, V.; SABOU, M. R.; MOTTA, E. Cross ontology query answering on the semantic web: an initial evaluation. In: ACM. Proceedings of the fifth international conference on Knowledge capture. [S. l.], 2009. p. 17–24.

MANOLA, F.; MILLER, E.; MCBRIDE, B. Rdf primer. w3c recommendation (2004). URL http://www. w3. org/TR/rdf-primer, 2004.

MENENDEZ, E. S.; CASANOVA, M. A.; LEME, L. A. P.; BOUGHANEM, M. Novel node importance measures to improve keyword search over rdf graphs. In: SPRINGER. International Conference on Database and Expert Systems Applications. [S. l.], 2019. p. 143–158. NADEAU, D.; SEKINE, S. A survey of named entity recognition and classification. Lingvisticae Investigationes, John Benjamins, v. 30, n. 1, p. 3–26, 2007.

OUKSILI, H.; KEDAD, Z.; LOPES, S.; NUGIER, S. Pattern oriented RDF graphs exploration. Data and Knowledge Engineering, Elsevier B.V., v. 113, n. March 2017, p. 116–128, 2018. ISSN 0169023X. Disponível em: <https://doi.org/10.1016/j.datak.2017.06.003>.

PERES, L.; SILVA, T. L. C. da; MACEDO, J.; ARAUJO, D. Ontology-schema based query by example. In: SPRINGER. International Conference on Conceptual Modeling. [S. l.], 2019. p. 204–212.

PERES, L.; SILVA, T. L. C. da; MACEDO, J.; ARAUJO, D. Virtualized ontology query by example. In: ER Forum and Poster Demos Session 2019. [S. l.: s. n.], 2019. p. 148–153.

PRIM, R. C. Shortest connection networks and some generalizations. Bell Labs Technical Journal, Wiley Online Library, v. 36, n. 6, p. 1389–1401, 1957.

PRUD’HOMMEAUX, E.; SEABORNE, A. et al. Sparql query language for rdf. w3c. Internet: https://www. w3. org/TR/rdf-sparql-query/[Accessed on April 5 th, 2017], 2008.

SAHA, D.; FLORATOU, A.; SANKARANARAYANAN, K.; MINHAS, U. F.; MITTAL, A. R.; ÖZCAN, F. Athena: an ontology-driven system for natural language querying over relational data stores. Proceedings of the VLDB Endowment, VLDB Endowment, v. 9, n. 12, p. 1209–1220, 2016.

SILVA, T. L. C. da; MAGALHÃES, R. P.; MACÊDO, J. A. de; MELO, V. de; REGO, P.; NETO, A. V. L. Improving named entity recognition using deep learning with human in the loop. In: EDBT. [S. l.: s. n.], 2019.

SINHA, S. B.; LU, X.; THEODORATOS, D. Personalized Keyword Search on Large RDF Graphs based on Pa ern Graph Similarity. 2018.

SOYLU, A.; KHARLAMOV, E.; ZHELEZNYAKOV, D.; JIMENEZ-RUIZ, E.; GIESE, M.; HORROCKS, I. Optiquevqs: Ontology-based visual querying. In: VOILA@ ISWC. [S. l.: s. n.], 2015. p. 91.

UNGER, C.; BÜHMANN, L.; LEHMANN, J.; NGOMO, A.-C. N.; GERBER, D.; CIMIANO, P. Template-based question answering over rdf data. In: ACM. Proceedings of the 21st international conference on World Wide Web. [S. l.], 2012. p. 639–648.

UNGER, C.; CIMIANO, P.; LOPEZ, V.; MOTTA, E. QALD-1 open challenge, 2011. USBECK, R.; NGOMO, A.-C. N.; BÜHMANN, L.; UNGER, C. Hawk–hybrid question answering using linked data. In: SPRINGER. European Semantic Web Conference. [S. l.], 2015. p. 353–368.

WINKLER, W. E. The state of record linkage and current research problems. In: CITESEER. Statistical Research Division, US Census Bureau. [S. l.], 1999.

XU, K.; ZHANG, S.; FENG, Y.; ZHAO, D. Answering natural language questions via phrasal semantic parsing. In: Natural Language Processing and Chinese Computing. [S. l.]: Springer, 2014. p. 333–344.

YADAV, V.; BETHARD, S. A survey on recent advances in named entity recognition from deep learning models. arXiv preprint arXiv:1910.11470, 2019.

YAHYA, M.; BERBERICH, K.; ELBASSUONI, S.; RAMANATH, M.; TRESP, V.; WEIKUM, G. Natural language questions for the web of data. In: ASSOCIATION FOR COMPUTATIONAL LINGUISTICS. Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning. [S. l.], 2012. p. 379–390.

YIH, S. W.-t.; CHANG, M.-W.; HE, X.; GAO, J. Semantic parsing via staged query graph generation: Question answering with knowledge base. 2015.

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