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Deep Learning powered Text Summarization Framework for creating a highly accurate summary
~ Dr. Subhra Jyoti Mandal
In modern age, free text data draws lot of attention. It’s increasing exponentially day-by-day. But behind the hype there’s a simple story. For decades, companies have been making decisions based on the structured, transactional data. Free text data was regarded as worthless. But with the advent of technology, the trend has changed. Now, the enterprises have realized that the unstructured data can be managed for analysis and better business decision making.
Today, the industry is experiencing an explosion in the amount of free text data, which is generated from a variety of sources such as email, blogs, documents, news, chats, scanned pdfs, social media, etc. This text base is an invaluable source of information and knowledge, which needs to be effectively curated and summarized for being useful. “Text summarization is the process of automatically generating natural language summaries from an input document while retaining the important points.” The summarized text is appended as metadata to the digitized asset. This process helps in easy and fast search as well as retrieval of information.
To derive real business value from free text data, you need the right framework to capture and organize a wide variety of data types from different sources, and to be able to easily summarize it within the context of the enterprise data. Deep Learning helps in the broadest and most integrated text summarization to acquire and organize these diverse data types and analyze them alongside the existing data to find new insights and capitalize on hidden relationships.