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@article{157081,
        author = {B.Rayudu and Dr. P. Sujatha},
        title = {Extracting and Ranking aspects from customers reviews using natural language processing Techniques},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {6},
        pages = {17-21},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=157081},
        abstract = {Now-a-days, shopper’s reviews are playing the most significant role on the society not only for customers but also production companies. A huge amount of customer reviews are available everywhere. These reviews are terribly useful to induce quality information about concern product and its aspects. Here Aspects are the features or components or attributes of a service or product. Aspects play the main role for products sometimes it can decide the product performances and its performance may impact on the product also. This article is proposed Aspect ranking model consisting of three phases i) Extract product aspects ii) Identify aspect sentiments iii) Aspects ranking. This model is useful for both customers and firms. The datasets used for this model are SemEval2014 restaurant, SemEval2014 laptop, Amazon canon G3 camera. The proposed model compared with the counter parts and achieves accurate results.},
        keywords = {Customer reviews, Aspect Extraction, Sentiment Analysis, Aspect based Sentiment Analysis, Product Aspects, Aspect Polarities, Abstract Syntax Tree, Pos Tag, Bag of words, Aspect Ranking },
        month = {},
        }