Survey on Multi-Document Summarizer
Abstract: Natural language processing provides Text Summarization which is the most popular application for information compression. Text summarization is a process of producing a summary by reducing the size of original document and pertaining important information of original document. There is arising a need to provide high quality summary in less time because in present time, the growth of data increases tremendously on World Wide Web or on users desktops so Multi-Document summarization is the best tool for making summary in less time. This paper presents a survey of existing techniques with the novelties highlighting the need of intelligent Multi-Document summarizer.
Keywords: Multi-Document Summarization, Clustering Based, Extractive and ive approach, Ranked Based, LDA Based, Natural Language Processing
How to Cite?: Prachi M. Joshi, Rupali R. Kadam, "Survey on Multi-Document Summarizer", Volume 3 Issue 12, December 2014, International Journal of Science and Research (IJSR), Pages: 1250-1254, https://www.ijsr.net/getabstract.php?paperid=SUB14697, DOI: https://dx.doi.org/10.21275/SUB14697