Clustering of People in Social Network based on Textual Similarity

Publication date: Available online 4 July 2016 Source:Perspectives in Science Author(s): Kuldeep Singh, Harish Kumar Shakya, Bhaskar Biswas With the growing importance for analysis of the textual similarity and between the user contents, we have highlighted textual similarity between various people in a social network. Words used in social sites are used for finding textual similarity. On the basis of the common words used in social networks, we have formulated a metric. The data has been extracted from social networking sites and then it is processed for generating the metrics. We compare simple k-means and spectral k-means algorithms for finding textual similarity. We have used WordNet to groups words together based on their meanings.

Source: Perspectives in Science - July 14, 2016 Category: Science Source Type: research