Text Summarization for Social Network Conversation

The proposed system discuss a text summarization system over the social web site. The proposed system works by assigning scores to sentences in the document to be summarized, and using the highest ranking sentences in the summary. Highest ranking values are based on features extracted from the sentence. A linear combination of feature scores is used. In addition to basic summarization, some attempt is made to address the issue of targeting the text at the user. The intended user is considered to have little background knowledge or reading ability. The system helps by simplifying the individual words used in the summary. In the proposed system, classification of keywords by higher ranking of topics has contributed to an active role for the extraction of summarization, the results of summarization ratio in social web is 40%-50%.