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Study of automatic text summarization approaches in different languages

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Abstract

Nowadays we see huge amount of information is available on both, online and offline sources. For single topic we see hundreds of articles are available, containing vast amount of information about it. It is really a difficult task to manually extract the useful information from them. To solve this problem, automatic text summarization systems are developed. Text summarization is a process of extracting useful information from large documents and compressing them into short summary preserving all important content. This survey paper hand out a broad overview on the work done in the field of automatic text summarization in different languages using various text summarization approaches. The focal centre of this survey paper is to present the research done on text summarization on Indian languages such as, Hindi, Punjabi, Bengali, Malayalam, Kannada, Tamil, Marathi, Assamese, Konkani, Nepali, Odia, Sanskrit, Sindhi, Telugu and Gujarati and foreign languages such as Arabic, Chinese, Greek, Persian, Turkish, Spanish, Czeh, Rome, Urdu, Indonesia Bhasha and many more. This paper provides the knowledge and useful support to the beginner scientists in this research area by giving a concise view on various feature extraction methods and classification techniques required for different types of text summarization approaches applied on both Indian and non-Indian languages.

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  1. Department of Computer Science & Engineering, Chandigarh Group of Colleges, Landran, Mohali, India

    Yogesh Kumar

  2. Department of Electronic & Communications, Punjabi University, Patiala, India

    Komalpreet Kaur

  3. Department of Computer Science & Engineering, Chandigarh Engineering College, Landran, Mohali, India

    Sukhpreet Kaur

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  1. Yogesh Kumar
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Kumar, Y., Kaur, K. & Kaur, S. Study of automatic text summarization approaches in different languages. Artif Intell Rev 54, 5897–5929 (2021). https://doi.org/10.1007/s10462-021-09964-4

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