ANN based ranking algorithm for products on E-Commerce website

Parashar, Aditya; Gupta, Eshan

doi:10.1109/aeeicb.2017.7972332

Cited by 4 publications

(3 citation statements)

References 5 publications

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“…In Parashar and Gupta's study [16], the customer of an E-commerce site has no real way to evaluate the quality of an acknowledged item to peruse an enormous number of reviews. This exploration work centers on building up a basic leadership calculation which can assess the nature of an item by sorting past surveys on a size of numbers and showing it on an E-commerce site.…”

Section: Literature Reviewmentioning

confidence: 99%

Ranking Analysis for Online Customer Reviews of Products Using Opinion Mining with Clustering

et al. 2018

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Sites for web-based shopping are winding up increasingly famous these days. Organizations are anxious to think about their client purchasing conduct to build their item deal. Internet shopping is a method for powerful exchange among cash and merchandise which is finished by end clients without investing a huge energy spam. The goal of this paper is to dissect the high-recommendation web-based business sites with the help of a collection strategy and a swarm-based improvement system. At first, the client surveys of the items from web-based business locales with a few features were gathered and, afterward, a fuzzy c-means (FCM) grouping strategy to group the features for a less demanding procedure was utilized. Also, the novelty of this work—the Dragonfly Algorithm (DA)—recognizes ideal features of the items in sites, and an advanced ideal feature-based positioning procedure will be directed to discover, at long last, which web-based business webpage is best and easy to understand. From the execution, the outcomes demonstrate the greatest exactness rate, that is, 94.56% compared with existing methods.

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Section: Literature Reviewmentioning

confidence: 99%

Ranking Analysis for Online Customer Reviews of Products Using Opinion Mining with Clustering

et al. 2018

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“…Customers can make use of this ranks provided with products over any E-Commerce website to make their own decisions. [5] This web site was created for the sole purpose -to implement and test all main SEO techniques. The main objective of this paper is to find whether search engine optimization increases rank of website in search results and subsequently leads to bigger traffic.…”

Section: Research Workmentioning

confidence: 99%

Review of Different Approaches for E-Commerce Website Ranking

Palwekar¹

2018

IJRASET

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In recent years E-commerce industry has grown rapidly. With the assistance of data mining and its integration with Ecommerce technology, organizations are increasing their revenues day by day and they are able to attract new customers. Enterprises are deploying new strategies to retain or rebuild relations with their old customers and persistently focusing on new customers. By these strategies enterprises are permeating themselves. Keeping in mind the thought of blending of data mining and E-commerce a tool, "E-Commerce Website Priority Determination Tool" that can extract keywords, links, and HTML tags of various websites with comparable statistics, with the help of which data analyst can find out the problems areas or missing important links or keywords in their websites to restructure their websites. The purpose of this paper is to discuss some of the earlier proposed Ecommerce website ranking technology, models and concept of webpage recommendation.

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“…The approach of ANN based ranking algorithm for products on E-commerce website [11] was given by Aditya parashar and Eshan gupta, this approach is similar to the proposed solution. It was a theoretical description of the current problem.…”

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confidence: 99%

ANN Based Recommendation Algorithm for the Product of E-commerce

Parashar¹,

Gupta²

2017

IJARCSSE

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Abstract-E-commerce websites have millions of product and billions of the reviews given by users on the products. The reviews are given by authentic and fake reviewers. If the customer read some reviews among them to check the quality of the product, he/she may get confuse. If customer gets bad quality product it get hearted and the image of the E-commerce site degrades. Another problem here is that the reviews are huge in numbers for a single product. To process these reviews E-commerce requires a big quality analysis team, which will be costly for the stakeholders. This paper gives the solution of this problem by doing some automation using artificial neural network. Proposed work is divided into two modules in first half neural net gives its output and in second half all the output is taken and calculate its mean, this mean makes able to the rank the product, that by how much percent it is saleable. Ultimately believe of the customer will maintain and it will not think for other option.Keywords-Ecommerce, User reviews, Product rank, Artificial Neural Network, Back Propagation I. INTRODUCTIONE-commerce is the platform of buying and selling of product, today"s era everybody wants to do shopping on Ecommerce because of it gives comfort, cost effective items, variety etc. Seeking this type of facility people do shopping on E-commerce platform. Apart from that today everybody talks about quality of service, everyone needs good product after paying some amount from its precious income. Today E-commerce is a huge platform to fulfil the customer demands, E-commerce persons should also maintains the quality of its products and they have very good team of quality check and assurance team but there are millions of product launches on their platform which are worldwide favourite brands but the quality of these brands may be good or it may not be good according to the customer"s expectations, after all customer is the end user of the particular product so it gives its reviews about that particular product on the site so the other customer may easily seek the information about that particular product. Some of the customer does not purchase the item if it has not good reviews given by the user, this kind of products which do not have good reviews may harms the image of the E-commerce site in front of its customer and customer may deviate to the other option and this will not be good for that organization.Artificial neural network is the better solution for that problem where some decision has to be made or problem requires some solution or classification. This problem will help to solve the problem of the E-commerce person to know the product quality which launches on their platform. If the product quality is not good according to its customer reviews, the action can be taken by E-commerce persons by removing the product form its site or by intimating the concerning product related company to maintain its product quality. These customer reviews are processed by the neural network and it will give some solution about the pro...

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ANN based ranking algorithm for products on E-Commerce website

Cited by 4 publications

References 5 publications

Ranking Analysis for Online Customer Reviews of Products Using Opinion Mining with Clustering

Ranking Analysis for Online Customer Reviews of Products Using Opinion Mining with Clustering

Review of Different Approaches for E-Commerce Website Ranking

ANN Based Recommendation Algorithm for the Product of E-commerce

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