Automatic acquisition of hyponyms from large text corpora. ACM SIGKDD Explorations Newsletter, 11(1), 10-18. The weka data mining software: an update. Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.Semi-automatic construction of topic ontologies. Fortuna, B., Mladeni¿, D., Grobelnik, M.In Proceedings of the 4th web as corpus workshop (WAC-4) can we beat Google (pp. Introducing and evaluating ukwac, a very large web-derived corpus of english. Ferraresi, A., Zanchetta, E., Baroni, M., Bernardini, S.In Proceedings of the EACL 2006 workshop on learning structured information in natural language applications (pp. Learning to identify definitions using syntactic features. Progress in Artificial Intelligence, 659-670. Automatic extraction of definitions in portuguese: a rule-based approach. ACM Transactions on Information Systems, 25(2). Soft pattern matching models for definitional question answering. In Proceedings of the 2008 ACM workshop on search in social media (pp. Creating tag hierarchies for effective navigation in social media. Ontology Learning from Text: Methods, Evaluation and Applications, 123, 3-12. Ontology learning from text: an overview. Buitelaar, P., Cimiano, P., Magnini, B.Association for Computational Linguistics. In Proceedings of the 1st workshop on definition extraction (pp. Evolutionary algorithms for definition extraction. In Proceedings of information systems: a crossroads for organization, management, accounting and engineering (ITAIS) conference. Eunomos, a legal document and knowledge management system for regulatory compliance. Boella, G., Martin, M., Rossi, P., van der Torre, L., Violato, A.In Theory, practice, and applications of rules on the web (pp. Semantic relation extraction from legislative text using generalized syntactic dependencies and support vector machines. In Machine learning and knowledge discovery in databases (pp. Supervised learning of syntactic contexts for uncovering definitions and extracting hypernym relations in text databases. In Proceedings of the 8th international conference on language resources and evaluation (LREC). Nlp challenges for eunomos, a tool to build and manage legal knowledge. Boella, G., di Caro, L., Humphreys, L., Robaldo, L., van der Torre, L.Ontology learning from text: a survey of methods. In Proceedings of the 10th international conference on artificial intelligence and law: ICAIL (pp. Automatic semantics extraction in law documents. Biagioli, C., Francesconi, E., Passerini, A., Montemagni, S., Soria, C.In Annual meeting association for computational linguistics (Vol. Then, we focus on the identification of hypernym relations and definitional sentences, demonstrating the validity of the approach on different tasks and domains. We first tested our technique on the problem of automatically extracting semantic entities and involved objects within legal texts. These new featured data are finally fed into a Support Vector Machine classifier that computes a model to automate the semantic annotation. Then, we transform these information into generalized features that aim at capturing the surrounding linguistic variability of the target semantic units. To achieve this goal, we propose an approach that first relies on well-known Natural Language Processing techniques like Part-Of-Speech tagging and Syntactic Parsing. In this work, we face the problem of automatically extracting structured knowledge to improve semantic search and ontology creation on textual databases. In a more domain-specific scenario like the management of legal documents, the extraction of semantic knowledge can support domain engineers to find relevant information in more rapid ways, and to provide assistance within the process of constructing application-based legal ontologies. This Big Data Era created novel challenges to be faced in order to make sense of large data storages as well as to efficiently find specific information within them. Nowadays, there is a huge amount of textual data coming from on-line social communities like Twitter or encyclopedic data provided by Wikipedia and similar platforms.
0 kommentar(er)
