A Novel Approach of Text Summarization using Assamese WordNet

Automatic Text Summarization techniques in Assamese language is still in an immature stage compared to other Indian languages. In this study, we have reviewed some of the studies in other Indian languages for having a better understanding of the problems. Furthermore, we have also put in our efforts to understand keeping in view the opinion of Assamese linguists as how we could overcome the shortcomings of Assamese Text Summarization and provide an effective solution that could serve as fundamental concepts in this particular field. An extractive method for text summarization is proposed in this paper to evaluate the sentences of the input document based on the merging of semantic and statistical characteristics. It is applied considering the importance of sentence and diversity. Moreover, we have applied Synsets from Assamese WordNet to calculate the word frequency. Besides identifying and weighing the salience sentences, the concept of vector centrality and cosine similarity is used and the result is represented in graph representation. A threshold value to indicate the important sentences is applied. The effectiveness of our proposed method is demonstrated through a set of experiments conducted using ROUGE measure and the evaluation is showed in terms of Recall.