{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T15:26:49Z","timestamp":1772033209335,"version":"3.50.1"},"reference-count":27,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2020,7,1]],"date-time":"2020-07-01T00:00:00Z","timestamp":1593561600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Regional Research and Innovation Strategies for Smart Specialization\u2014RIS3 in Information and Communication Technologies","award":["5038701"],"award-info":[{"award-number":["5038701"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Text annotation is the process of identifying the sense of a textual segment within a given context to a corresponding entity on a concept ontology. As the bag of words paradigm\u2019s limitations become increasingly discernible in modern applications, several information retrieval and artificial intelligence tasks are shifting to semantic representations for addressing the inherent natural language polysemy and homonymy challenges. With extensive application in a broad range of scientific fields, such as digital marketing, bioinformatics, chemical engineering, neuroscience, and social sciences, community detection has attracted great scientific interest. Focusing on linguistics, by aiming to identify groups of densely interconnected subgroups of semantic ontologies, community detection application has proven beneficial in terms of disambiguation improvement and ontology enhancement. In this paper we introduce a novel distributed supervised knowledge-based methodology employing community detection algorithms for text annotation with Wikipedia Entities, establishing the unprecedented concept of community Coherence as a metric for local contextual coherence compatibility. Our experimental evaluation revealed that deeper inference of relatedness and local entity community coherence in the Wikipedia graph bears substantial improvements overall via a focus on accuracy amelioration of less common annotations. The proposed methodology is propitious for wider adoption, attaining robust disambiguation performance.<\/jats:p>","DOI":"10.3390\/a13070160","type":"journal-article","created":{"date-parts":[[2020,7,2]],"date-time":"2020-07-02T02:44:25Z","timestamp":1593657865000},"page":"160","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Text Semantic Annotation: A Distributed Methodology Based on Community Coherence"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2571-7449","authenticated-orcid":false,"given":"Christos","family":"Makris","sequence":"first","affiliation":[{"name":"Department of Computer Engineering and Informatics, University of Patras, 26504 Patras, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9765-5542","authenticated-orcid":false,"given":"Georgios","family":"Pispirigos","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering and Informatics, University of Patras, 26504 Patras, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9012-8240","authenticated-orcid":false,"given":"Michael Angelos","family":"Simos","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering and Informatics, University of Patras, 26504 Patras, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,7,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.physrep.2009.11.002","article-title":"Community detection in graphs","volume":"486","author":"Fortunato","year":"2010","journal-title":"Phys. Rep."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Blondel, V.D., Guillaume, J.-L., Lambiotte, R., and Lefebvre, E. (2008). Fast unfolding of communities in large networks. J. Stat. Mech. Theory Exp., 10008.","DOI":"10.1088\/1742-5468\/2008\/10\/P10008"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"066111","DOI":"10.1103\/PhysRevE.70.066111","article-title":"Finding community structure in very large networks","volume":"70","author":"Clauset","year":"2004","journal-title":"Phys. Rev. E"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1459352.1459355","article-title":"Word sense disambiguation: A survey","volume":"41","author":"Navigli","year":"2009","journal-title":"ACM Comput. Surv."},{"key":"ref_5","unstructured":"Mallery, J.C. (1988). Thinking about Foreign Policy: Finding an Appropriate Role for Artificial Intelligence Computers. [Ph.D. Thesis, MIT Political Science Department]."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1007\/BF00136984","article-title":"A method for disambiguating word senses in a large corpus","volume":"26","author":"Gale","year":"1992","journal-title":"Comput. Humanit."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Mihalcea, R., and Csomai, A. (2007, January 6\u20138). Wikify! Linking Documents to Encyclopedic Knowledge. Proceedings of the CIKM 2007, Lisboa, Portugal.","DOI":"10.1145\/1321440.1321475"},{"key":"ref_8","unstructured":"Silviu, C. (2007, January 28\u201330). Large-Scale Named Entity Disambiguation Based on Wikipedia Data. Proceedings of the EMNLP-CoNLL 2007, Prague, Czech."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Milne, D., and Witten, I. (2008, January 26\u201330). Learning to link with wikipedia. Proceedings of the 17th ACM Conference on Information and Knowledge Management, Napa Valley, CA, USA.","DOI":"10.1145\/1458082.1458150"},{"key":"ref_10","unstructured":"Milne, D.N., and Witten, I. (2008). An Effective, Low-cost Measure of Semantic Relatedness Obtained from Wikipedia Links, AAAI Workshop on Wikipedia and Artificial Intelligence."},{"key":"ref_11","unstructured":"Kulkarni, S., Singh, A., Ramakrishnan, G., and Chakrabarti, S. (July, January 28). Collective annotation of Wikipedia entities in web text. Proceedings of the 15th ACM SIGKDD International Conference, Paris, France."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Ferragina, P., and Scaiella, U. (2010, January 26\u201330). TAGME: On-the-fly annotation of short text fragments (by wikipedia entities). Proceedings of the 19th ACM International Conference on Information and Knowledge Management 2010, Toronto, ON, Canada.","DOI":"10.1145\/1871437.1871689"},{"key":"ref_13","unstructured":"Hoffart, J., Yosef, M.A., Bordino, I., F\u00fcrstenau, H., Pinkal, M., Spaniol, M., Taneva, B., Thater, S., and Weikum, G. (2011, January 27\u201331). Robust Disambiguation of Named Entities in Text. Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, Edinburgh, UK."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Han, X., Sun, L., and Zhao, J. (2011, January 25\u201329). Collective entity linking in web text: A graph-based method. Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, Beijing, China.","DOI":"10.1145\/2009916.2010019"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Usbeck, R., Ngomo, A.-C.N., R\u00f6der, M., Gerber, D., Coelho, S.A., Auer, S., and Both, A. (2014, January 18\u201322). AGDISTIS\u2014Agnostic Disambiguation of Named Entities Using Linked Open Data. Proceedings of the ECAI 2014 21st European Conference on Artificial Intelligence, Prague, Czech.","DOI":"10.1007\/978-3-319-11964-9_29"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Piccinno, F., and Ferragina, P. (2014, January 11). From TagME to WAT: A new entity annotator. Proceedings of the First International Workshop on Entity Recognition & Disambiguation, Gold Coast Queensland, Australia.","DOI":"10.1145\/2633211.2634350"},{"key":"ref_17","unstructured":"Sun, Y., Lin, L., Tang, D., Yang, N., Ji, Z., and Wang, X. (2015, January 25\u201331). Modeling Mention, Context and Entity with Neural Networks for Entity Disambiguation. Proceedings of the IJCAI 2015 Twenty-Fourth International Joint Conference on Artificial Intelligence, Buenos Aires, Argentina."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Yamada, I., Shindo, H., Takeda, H., and Takefuji, Y. (2016). Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation. arXiv.","DOI":"10.18653\/v1\/K16-1025"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Ganea, O.-E., and Hofmann, T. (2017). Deep joint entity disambiguation with local neural attention. arXiv.","DOI":"10.18653\/v1\/D17-1277"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Sil, A., Kundu, G., Florian, R., and Hamza, W. (2018). Neural Cross-Lingual Entity Linking. arXiv.","DOI":"10.1609\/aaai.v32i1.11964"},{"key":"ref_21","unstructured":"Shnayderman, I., Ein-Dor, L., Mass, Y., Halfon, A., Sznajder, B., Spector, A., Katz, Y., Sheinwald, D., Aharonov, R., and Slonim, N. (2019). Fast End-to-End Wikification. arXiv."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Rasmussen, C.E., and Williams, C.K. (2006). Gaussian Processes for Machine Learning, MIT Press.","DOI":"10.7551\/mitpress\/3206.001.0001"},{"key":"ref_23","unstructured":"(2020, May 05). Index of \/enwiki\/. Available online: https:\/\/dumps.wikimedia.org\/enwiki."},{"key":"ref_24","unstructured":"(2020, May 05). Clauset-Newman-Moore Algorithm Implementation. Available online: https:\/\/networkx.github.io\/documentation\/stable\/_modules\/networkx\/algorithms\/community\/modularity_max.html#greedy_modularity_communities."},{"key":"ref_25","unstructured":"(2020, May 05). Louvain Algorithm Implementation. Available online: https:\/\/github.com\/Sotera\/spark-distributed-louvain-modularity."},{"key":"ref_26","unstructured":"(2020, May 05). sklearn.gaussian_process.GaussianProcessClassifier. Available online: https:\/\/scikit-learn.org\/stable\/modules\/generated\/sklearn.gaussian_process.GaussianProcessClassifier.html."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Makris, C., Pispirigos, G., and Rizos, I.O. (2020). A Distributed Bagging Ensemble Methodology for Community Prediction in Social Networks. Information, 11.","DOI":"10.3390\/info11040199"}],"container-title":["Algorithms"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-4893\/13\/7\/160\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:45:40Z","timestamp":1760175940000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-4893\/13\/7\/160"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,7,1]]},"references-count":27,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2020,7]]}},"alternative-id":["a13070160"],"URL":"https:\/\/doi.org\/10.3390\/a13070160","relation":{},"ISSN":["1999-4893"],"issn-type":[{"value":"1999-4893","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,7,1]]}}}