Text Summarization Using Deep Learning

Student: Kondratenkov Pavel

Supervisor: Ekaterina Artemova

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Year of Graduation: 2018

In this article a new dataset for text summarization in Russian language is introduced with the description of the method for obtaining dataset and its main features. It contains popular science articles from site N+1. We estimated the baseline ROUGE scores for the considered dataset with the use of TextRank algorithm and compared the performance of various similarity functions: frequency-based and ones that takes into account the semantic of the words. The best performance is achieved using the modification of the BM25 metrics.

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