Application

Text summarization is used by search engines for short-circuiting responses to queries, generating product descriptions, synopses and abstracts. While almost any business could benefit from expediting their processes, cost-effective and accurate summarization is of special interest to industries reliant on large-scale information digestion such as:

• Finance, for processing credit card, loan or mortgage applications

• Academia, for constructing abstracts and assessing personal statements

• Large retailers or services, for analyzing public relations via online comments, reviews and tweets

• Real-estate agencies handling large amounts of unstructured text such as property descriptions, contracts, queries and complaints.

In summary, text summarization aims to reduce the time taken for a reader to understand a piece of text. This time can then be reinvested by the employee, increasing productivity to the business. An analysis at the University of Dusseldorf showed that providing media analysts with an automatically-generated summary of news articles “does not have a negative impact on the quality of the summaries they generated” and had a “significant gain in time by the process of creating the text summaries (58%)” [1]. The savings in employee time, focus and cost are self-evident.