Abstract
Nowadays, news portals are forced to seek new methods of engaging the audience due to the increasing competition in today’s mass media. The growth in the loyalty of news service consumers may further a rise of popularity and, as a result, additional advertising revenue. Therefore, we propose the tool that is intended for stylish presenting of facts from a news feed. Its outputs are little poems that contain key facts from different news sources, based on the texts of Russian classics. The main idea of our algorithm is to use a collection of classical literature or poetry as a dictionary of style. The facts are extracted from news texts through Tomita Parser and then presented in the form similar to a sample from the collection. During our work, we tested several approaches for text generating, such as machine learning (including neural networks) and template-base method. The last method gave us the best performance, while the texts generated by the neural network are still needed to be improved. In this article, we present the current state of Narrabat, a prototype system rephrasing news we are currently working on, give examples of generated poems, and discuss some ideas for future performance improvement.
Highlights
1.1 The main ideaIn the era of information explosion demand for news aggregation services is always high
Classical news services like Yandex News or Google News are on the market for a long time, but their format is too restricted to satisfy all potential audiences
The goal of the study is to develop a methodology of rewriting news texts in a specified style and to implement it as a service
Summary
In the era of information explosion demand for news aggregation services is always high. The goal of the study is to develop a methodology of rewriting news texts in a specified style and to implement it as a service. To provide a new insight into retelling news, we build an architecture of Narrabat that is rather straightforward: retrieve news from the providers, extract facts, reproduce the facts in a new form. It is necessary to process the news and extract the main information from it. At this point, it is essential to realize what kind of unstructured data will be marked as key information. The paper presents the current state of the retelling service implementation we are still working on. The plan of the paper is the following: in section 2 we present an algorithm for producing poems from the news.
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