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@article{145504,
        author = {P.Chandana and Mr J S.Ananda Kumar},
        title = {Detection of Client patterns in social networks by data mining technique:Facebook case},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {4},
        number = {10},
        pages = {487-490},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=145504},
        abstract = {Data mining is the practice of automatically searching large stores of data to discover patterns and trends that go beyond simple analysis. Data mining uses sophisticated mathematical algorithms to segment the data and evaluate the probability of future events. Data mining is also known as Knowedge Discovery in Data (KDD). Today Facebook is considered as one of the most popular platforms for online social networking among youth, and - as many researches show – university students. The purpose of this study is to assess the impact of social networking sites i.e. Facebook on students’ academic performance. As the facebook provides rich opportunities for the users makes it popular social media. In this paper we mainly concentrate on what are the factors affecting the “facebook usage time” and “facebook access frequency” are calculated by using the apriori algorithm. This can calculate by collecting the data from the facebook users.},
        keywords = {Facebook, apriori algorithm, Data mining.},
        month = {},
        }