Abstract

We present our state of the art multilingual text summarizer capable of single as well as multi-document text summarization. The algorithm is based on repeated application of TextRank on a sentence similarity graph, a bag of words model for sentence similarity and a number of linguistic pre- and post-processing steps using standard NLP tools. We submitted this algorithm for two different tasks of the MultiLing 2015 summarization challenge: Multilingual Singledocument Summarization and Multilingual Multi-document Summarization.

Keywords:
Automatic summarization Computer science Natural language processing Text graph Similarity (geometry) Artificial intelligence Sentence Multi-document summarization Information retrieval Graph Theoretical computer science

Metrics

10
Cited By
0.94
FWCI (Field Weighted Citation Impact)
24
Refs
0.88
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Topic Modeling
Physical Sciences →  Computer Science →  Artificial Intelligence
Natural Language Processing Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Text Analysis Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence

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