A Single Document Assamese Text Summarization Using a Combination of Statistical Features and Assamese WordNet

In this paper, an extractive text summarization approach using Assamese WordNet is proposed, and the difficulties faced while extracting summary in the Assamese document are discussed. The Assamese language is a low-level language. Synset is applied from Assamese WordNet. The various features used for identifying the most salient sentences to generate effective summary aspects such as TF-IDF, sentence length, sentence position and numerical identification are considered. Automatic Text Summarization in the Assamese language is still in an early stage and this language does not have its own approach. So, the text summarization approach is compared to the approaches applied in Bengali and Bangla language approaches as these languages share a script that is quite similar having slight variations in certain letters. The effectiveness of our proposed approach is demonstrated through a set of experiments carried out using ROUGE measure, and the evaluation is depicted in terms of Precision, Recall and F1-score.