Legal Case Summarization: An Application for Text Summarization
This research uses web scrapping technique that helps in direct extraction of data from online resources hence results in accurate results and concludes that LUHN and LSA are the two best algorithms according to the ROUGE-1 and RouGE-2 scores.
Abstract
Today in the realm of developing advances, there is a gigantic development in technologies. These days every single theme identified with research is accessible on the web. Consequently to profit the clients, it is required to condense the substance as short as possible. Different research networks are proposing enormous number of methods to abridge the substance. So in this exploration an extractive methodology is executed so as to save Indian lawyer’s time in dealing with the big cases. This research uses web scrapping technique that helps in direct extraction of data from online resources hence results in accurate results. This is done using python on ANACONDA to summarize the IT LAW cases which are extricated using web scrapping strategy. After the extraction, different techniques such as LUHN, LSA, LEXRANK and SUMBASIC are used to summarize the content and calculate the ROUGE scores. The exploration just compares these four techniques on the basis of their performance metrics of ROUGE-1 and ROUGE-2 scores and according to the precision, recall and f-measure scores finally concludes that LUHN and LSA are the two best algorithms according to the ROUGE-1 and ROUGE-2 scores.