Abstract—Understanding meanings and semantics of a speech or natural language is a complicated problem. This problem becomes more vital and classy when meanings with respect to context, have to be extracted. This particular research area has been typically point of meditation for the last few decades and many various techniques have been used to address this problem. An automated system is required that may be able to analyze and understand a few paragraphs in English language. In this research, Markov Logic has been incorporated to analyze and understand the natural language script given by the user. The designed system formulates the standard speech language rules with certain weights. These meticulous weights for each rule ultimately support in deciding the particular meaning of a phrase and sentence. The designed system provides an easy and consistent way to figure out speech language context and produce respective meanings of the text.
Index Terms—Text Processing, Markov Logic, Meaning Extraction, Language Engineering, Context Awareness.
Imran Sarwar Bajwa is with Department of Computer Science and IT, The Islamia University of Bahawalpur, Pakistan, Ph: +92 62 925 5466, imran.sarwar@iub.edu.pk
Cite: Imran Sarwar Bajwa, "Context Based Meaning Extraction by Means of Markov Logic," International Journal of Computer Theory and Engineering vol. 2, no. 1, pp. 35-38, 2010.
Copyright © 2008-2024. International Association of Computer Science and Information Technology. All rights reserved.
