Implementing Movie Supporter System Using  Query Processing On Partial Data

Implementing Movie Supporter System Using Query Processing On Partial Data
Author(s):
MARELLA SURESHBABU, MYLAPOOR MADHU
Keywords:
Partial data, Query processing Clustering, Collaborative Filtering, Movie Support System
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.
Article Details
Unique Paper ID: 146221 Publication Volume & Issue: Volume 4, Issue 11 Page(s): 1949 - 1954
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