Text Summarization in Sports Domain S. Jassem Mohammed(CB.EN.P2AID19016), Dharshan Vasanth(CB.EN.P2AID19008) Department of Computer Science Engineering, Amrita Vishwa Vidyapeetham Coimbatore, India jazzymohamed@gmail.com Abstract This report presents an overview of text summarization and how it can be utilized in the field of sports. Due to the great amount of information we are provided with and thanks to the development of Internet technologies, needs of producing summaries have become more and more widespread. Summa- rization is a very interesting and useful task that gives support to many other tasks as well as it takes advantage of the techniques developed for related Natural Language Processing tasks. 1. INTRODUCTION Generating a condensed version of a passage while preserving its mean- ing is known as text summarization. Tackling this task is an important step towards natural language understanding. Summarization systems can be broadly classified into two categories. Extractive models generate sum- maries by cropping important segments from the original text and putting them together to form a coherent summary. Abstractive models generate summaries from scratch without being constrained to reuse phrases from the original text. The task of a text summarizer is to produce a synopsis of any document (or set of documents) submitted to it. The level of sophistication of a synopsis can vary from a simple list of isolated keywords that indicate the major content of the document, through a list of independent single sen- tences that together express the major content, to a coherent, fully planned and generated text that compresses the document. The more sophisticated a synopsis, the more effort it generally takes to produce.