Markov logic for statistical relation extraction
Seneviratne et al. · International Journal of ADVANCED AND APPLIED SCIENCES · 2020
In today's world, the Internet has become a fast and efficient information provider, although the relevancy or accuracy of the information found is not guaranteed.The web itself presents numerous problems in finding a required piece of information, mainly due to its heterogeneous nature.Therefore, extracting information from the web is still a challenging task despite the fact that numerous work has been cited in the literature.Extracting information in the form of entities and relations has been addressed by various techniques such as machine learning, natural language processing, and statistical methods, etc.In this paper, we present a rulebased method which is hybridized by machine learning and statistical techniques for accurate performance in domain-specific relation extraction.The rules are modeled in Markov Logic Network to enable statistical performance.Our results on two test domains show overall high values in precision.