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Survey Paper | Computer Science Engineering | Volume 5 Issue 1, January 2016 | Pages: 240 - 242 | India
A Collective Study for Document Recommendation Using Textual Conversation Keywords
Abstract: Extraction is an important technique in many areas of document processing such as text clustering, text summarization, and text retrieval. s are viewed as the words that represent the topic and the content of the word. This paper addresses, the new technique for extraction from conversations fragment, which can be recommended to the participants to fulfill their information needs without distracting them. A short conversation fragment contains lots of words which can be related to several topics, so s are the index terms that contain most important information. In this paper, a survey of extraction technique have been presented that can be applied to extract the that uniquely identified the documents.
Keywords: Document recommendation, information retrieval, extraction, meeting analysis, topic modeling
How to Cite?: Snehalata M. Lad, Aruna Gupta, "A Collective Study for Document Recommendation Using Textual Conversation Keywords", Volume 5 Issue 1, January 2016, International Journal of Science and Research (IJSR), Pages: 240-242, https://www.ijsr.net/getabstract.php?paperid=NOV152670, DOI: https://dx.doi.org/10.21275/NOV152670