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Reseach Article

Using Dynamic Constraints Find Top Products

by Nihalahmad R.shikalgar, Dhanaji Jadhav
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 115 - Number 1
Year of Publication: 2015
Authors: Nihalahmad R.shikalgar, Dhanaji Jadhav

Nihalahmad R.shikalgar, Dhanaji Jadhav . Using Dynamic Constraints Find Top Products. International Journal of Computer Applications. 115, 1 ( April 2015), 44-47. DOI=10.5120/20119-2179

@article{ 10.5120/20119-2179,
author = { Nihalahmad R.shikalgar, Dhanaji Jadhav },
title = { Using Dynamic Constraints Find Top Products },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 115 },
number = { 1 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 44-47 },
numpages = {9},
url = { },
doi = { 10.5120/20119-2179 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T22:53:31.076685+05:30
%A Nihalahmad R.shikalgar
%A Dhanaji Jadhav
%T Using Dynamic Constraints Find Top Products
%J International Journal of Computer Applications
%@ 0975-8887
%V 115
%N 1
%P 44-47
%D 2015
%I Foundation of Computer Science (FCS), NY, USA

The growing popularity of online product review forums invites people to express opinions and purchase their products. In variety of different item set, it is very difficult to analysis skyline product from the set of different product. A consumer electronics world, product should consisting of varieties in color, functionality, applicability, reasonability, there look and all. It is unpredictable to select a product from pool of given product. In multi-criteria decision making application, most previous studies focus on how to help customers find a set of best possible , profitable products from a pool of given products. In this paper, we identify an interesting problem, using dynamic constraint find top k product, which has not been studied before. Given a set of products in the existing market, we want to find a set of "best" possible products such that these new products are not dominated by the products in the existing market. A straightforward solution is to enumerate all possible subsets of size k and find the subset which gives the greatest profit. However, there are an exponential number of possible subsets. In this paper, we propose solutions to find the top-k products efficiently by considering. An extensive performance study using both synthetic and real datasets is reported to verify its effectiveness and efficiency.

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Computer Science
Information Sciences


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