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@article{143109,
        author = {Tushar Mehmi},
        title = {Online Comment Analysis for Recommendation},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {2},
        number = {7},
        pages = {636-640},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=143109},
        abstract = {This Research  paper  analysis  the use of soft computing techniques to develop recommendation systems.  Information on the Internet grows rapidly and users should be directed to high quality Websites those are relevant to their personal interests. However, there is no way to Judge these web pages. Displaying quality content to users based on ratings or past Search results are not adequate. There’s a lacking of powerful automated process combining human opinions with machine learning of personal preference. The ongoing rapid expansion of the Internet greatly increases the necessity of effective recommender systems for filtering the abundant information. Extensive research for recommender systems is conducted by a broad range of communities including social and computer scientists, physicists, and interdisciplinary researchers. Despite substantial theoretical and practical achievements, unification and comparison of different approaches are lacking, which impedes further advances.},
        keywords = {Automated Collaborative Filtering (ACF),collaborative filtering (CF)},
        month = {},
        }