出版社：Vilnius University, University of Latvia, Latvia University of Agriculture, Institute of Mathematics and Informatics of University of Latvia
摘要：There exist distinctive words that are used to express same semantics and as a result of
this it has become hard to quantify the exact matching of words. To deal with this issue, past
investigations endeavored to ascertain a likeness between distinctive pair of words. Conventional
methodologies for computing word similarity are based on repositories like WordNet. It is a
manually created lexical database and it processes semantic connection between various words.
However, WordNet is a universally useful asset but wide range of words are not present in it and
furthermore there exist an issue of identifying the meaning of words. Implication of words are
diverse in WordNet when we utilize it in a textual framework. There exists a need of the refined
approach that can gauge words resemblance in light of their co-occurrence. In this examination,
we proposed an approach that registers likeness in text particular words, with the assistance of
literary substance of various posts on StackOverflow. Our proposed strategy figures out word
similarities in text by ascertaining the weighted co-occurrence in view of Computing Term Cooccurrence
(CTC) and SentiWordNet. The exploratory outcome demonstrates that our system
proposed an arrangement of words that are identified with text data is exceptional. Moreover,
when it was compared with WordNet-based strategy named as WordNetres, it results with better
outcomes.
关键词：Social Media; Natural Language Processing (NLP); WordNet;
