Abstract
Duplicate publication and plagiarism are two major problems in scholarly world and even they are called the cancer of academia. Plagiarism detection systems try to find similar publications of a specific article; yet, there is a little advance in holistic plagiarism detection systems. Text similarity services, without a human manual confirmation, are not capable to confirm duplication; nonetheless, it is achievable to develop a system that determines the probability of an infringement. In this paper we introduce a technique to develop such systems by using probabilistic ontologies and reasoning. The output of this system can be used for statistical surveys about rate of prevalence of plagiarism. As well, it can hit on the most probable cases of plagiarism for further investigation by human.
Keywords
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Encyclopedia of Database Systems, 1st edn. Springer (2009)
Poole, D., Smyth, C., Sharma, R.: Ontology design for scientific theories that make probabilistic predictions. IEEE Intelligent Systems 24(1), 27–36 (2009)
Haase, P., Völker, J.: Ontology Learning and Reasoning — Dealing with Uncertainty and Inconsistency. In: da Costa, P.C.G., d’Amato, C., Fanizzi, N., Laskey, K.B., Laskey, K.J., Lukasiewicz, T., Nickles, M., Pool, M. (eds.) URSW 2005 - 2007. LNCS (LNAI), vol. 5327, pp. 366–384. Springer, Heidelberg (2008)
Calì, A., Lukasiewicz, T., Predoiu, L., Stuckenschmidt, H.: Rule-Based Approaches for Representing Probabilistic Ontology Mappings. In: da Costa, P.C.G., d’Amato, C., Fanizzi, N., Laskey, K.B., Laskey, K.J., Lukasiewicz, T., Nickles, M., Pool, M. (eds.) URSW 2005 - 2007. LNCS (LNAI), vol. 5327, pp. 66–87. Springer, Heidelberg (2008)
Haarslev, V., Pai, H.-I., Shiri, N.: Uncertainty Reasoning for Ontologies with General TBoxes in Description Logic. In: da Costa, P.C.G., d’Amato, C., Fanizzi, N., Laskey, K.B., Laskey, K.J., Lukasiewicz, T., Nickles, M., Pool, M. (eds.) URSW 2005 - 2007. LNCS (LNAI), vol. 5327, pp. 385–402. Springer, Heidelberg (2008)
Foudeh, P., Salim, N.: Probabilistic ontologies and probabilistic ontology learning: Significance and challenges. In: 2011 International Conference on Research and Innovation in Information Systems (ICRIIS), pp. 1–4. IEEE (2011)
Halpern, J.Y.: Reasoning about uncertainty. MIT Press (2005)
Pearl, J.: Bayesian networks: A model of Self-Activated memory for evidential reasoning. In: Proceedings of the 7th Conference of the Cognitive Science Society, pp. 329–334. University of California, Irvine (1985)
Laskey, K.B.: MEBN: A language for first-order bayesian knowledge bases. Artificial Intelligence 172(2-3), 140–178 (2008)
Costa, P.C.G., Laskey, K.B.: PR-OWL: A framework for probabilistic ontologies. In: Proceeding of the 2006 conference on Formal Ontology in Information Systems: Proceedings of the Fourth International Conference (FOIS 2006), pp. 237–249. IOS Press, Amsterdam (2006)
Carvalho, R.N., Laskey, K., Costa, P.: Compatibility formalization between PR-OWL and OWL. In: First International Workshop on Uncertainty in Description Logics (2010)
Costa, P.C.G., Ladeira, M., Carvalho, R.N., Santos, L.L., Matsumoto, S., Laskey, K.B.: A First-Order bayesian tool for probabilistic ontologies. In: Proceedings of the Twenty-First International Florida Artificial Intelligence Research Society Conference, pp. 631–636. AAAI Press, Menlo Park (2008)
Carvalho, R.N., Ladeira, M., Santos, L.L., Matsumoto, Costa, P.C.G.: UnBBayes-MEBN: Comments on Implementing a Probabilistic Ontology Tool. In: Proceedings of the IADIS International Conference on Applied Computing, Algarve, Portugal, pp. 211–218 (2008)
Carvalho, R.N., Laskey, K.B., Costa, P., Ladeira, M., Santos, L.L., Matsumoto, S.: Probabilistic knowledge fusion for procurement fraud detection in Brazil (2009)
Deja vuresearch website, http://dejavu.vbi.vt.edu/dejavu
eTBLAST research website, http://etest.vbi.vt.edu/etblast3
Errami, M., Hicks, J.M., Fisher, W., Trusty, D., Wren, J.D., Long, T.C., Garner, H.R.: Déjà vu-a study of duplicate citations in medline. Bioinformatics 24(2), 243–249 (2008)
Errami, M., Sun, Z., Long, T.C., George, A.C., Garner, H.R.: Deja vu: a database of highly similar citations in the scientific literature. Nucleic Acids Research 37(Database issue), D921–D924 (2009)
Errami, M., Sun, Z., George, A.C., Long, T.C., Skinner, M.A., Wren, J.D., Garner, H.R.: Identifying duplicate content using statistically improbable phrases. Bioinformatics 26(11), 1453–1457 (2010)
Long, T.C., Errami, M., George, A.C., Sun, Z., Garner, H.R.: Scientific integrity responding to possible plagiarism. Science 323(5919), 1293–1294 (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Foudeh, P., Salim, N. (2012). A Holistic Approach to Duplicate Publication and Plagiarism Detection Using Probabilistic Ontologies. In: Hassanien, A.E., Salem, AB.M., Ramadan, R., Kim, Th. (eds) Advanced Machine Learning Technologies and Applications. AMLTA 2012. Communications in Computer and Information Science, vol 322. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35326-0_56
Download citation
DOI: https://doi.org/10.1007/978-3-642-35326-0_56
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35325-3
Online ISBN: 978-3-642-35326-0
eBook Packages: Computer ScienceComputer Science (R0)