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@article{146221,
        author = {MARELLA SURESHBABU and MYLAPOOR MADHU},
        title = {Implementing Movie Supporter System Using  Query Processing On Partial Data},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {4},
        number = {11},
        pages = {1949-1954},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=146221},
        abstract = {In this paper, we used Top-k Dominating (TKD) for partial query processing which returns the k objects that dominate the maximum number of objects in a given dataset. It combines the advantages of skyline and top-k queries, and plays an important role in many decision support applications. Partial data exists in a wide spectrum of real datasets, due to device failure, privacy preservation, data loss, and so on. In this paper, for the first time, we carry out a systematic study of TKD queries on Partial data, which involves the data having some missing dimensional value(s). Extensive experimental evaluation using both real and synthetic datasets demonstrates the effectiveness of our developed pruning heuristics and the performance of our presented algorithms. The purpose of this study is to develop a ‘Movie Support System’ with the help of Collaborative Filtering approach.},
        keywords = {Partial data, Query processing Clustering, Collaborative Filtering, Movie Support System},
        month = {},
        }