Text analytics through Summariser

Introduction of Text summary:

Text summarization is the process of identifying the most important meaningful information in a text document and compressing them into a shorter version preserving its overall meanings. Text Summarization is based on advanced Natural language processing and Machine Learning Technologies. It can be used to summarize text from URL or raw text document that user provided. Summarising is based on ranks of text sentences using a variation of the TextRank. Text cleaning and using different RegEx and NLP is necessary part of summarization.

In a similar way, it can also extract topics using topic modelling and LDA. For topic modelling used bigram and trigram after cleaning of text like removing stop words, lemmatisation etc.

Last step in summarisation API is to extract Financial Information from text. To extract financial facts from Text used Text processing, Spacy and NLTK library combining for more accurate Financial information.

Process of Summarisation:

 

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