Natural Language Processing focuses on several areas like:

Building computer programs that give data points with context.

Mine large quantities of numerical data

Patterns identification

Sharing information that is easy for humans to understand

Producing news and other time-sensitive stories available on the internet

The information is expanding exponentially in the World Wide Web. Hence, the extraction of valid and useful information from huge data has become a challenging issue. Text summarization is one of the best solutions for extracting relevant information from large documents. Depending on the number of documents considered for summarization, the summarization task is categorized into a single document or multi-document summarization.

Multi-document summarization is more challenging than a single-document summarization for the researchers to find an accurate summary from multiple documents.

The reasons why multi-document summarization is more complicated are:

Search space is larger as compared to single document summarization

Extraction of important sentences becomes more challenging

Compression of multiple documents

Speed of sentence extraction gets reduced

Redundancy between sentences and sentence selection

Some companies find it challenging and difficult to process the multi-document summarization, but RIS will assist you in every single step of this technique to reach your goals and make your business profitable.

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