Recommendation of Influenced Products Using Association Rule Mining: Neo4j as a Case Study
Sudipta Sen,Akash Mehta,Runa Ganguli,Soumya Sen +3 more
- Vol. 2, Iss: 2, pp 1-17
TLDR
In this paper, the authors proposed a new association rule mining technique for quick decision-making and it gives better performance over Apriori algorithm which is one of the most popular approaches for Association rule mining.Abstract:
Recommendation systems are now inherent for many business applications to take important business decisions. These systems are built based on the historical data that may be the sales data or customer feedback etc. Customer feedback is very important for any organization as it reflects the view, sentiment of the customers. Online systems allow customers to purchase products at a glance from any e-commerce website. Generally, the potential buyers check the review of the products to take informed decision of purchase. In this work, we attempt to build a recommendation model to find out the influence of a product on another product so that if a user purchases the influential product then the recommender system can recommend the influenced products to the users. In this paper, the recommendation system has been built based on association rule mining. We proposed a new association rule mining technique for quick decision-making and it gives better performance over Apriori algorithm which is one of the most popular approaches for association rule mining. The entire framework has been developed in Neo4j graph data model for doing the data modelling from raw text file and also to perform the analysis. We used real-life customer feedback data of amazon for experimental purpose.read more
Citations
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Journal ArticleDOI
Session-Based Recommendations for e-Commerce with Graph-Based Data Modeling
TL;DR: In this article , the authors proposed two session-based recommendation methods for anonymous browsing in a generic e-commerce framework, Hierarchical Sequence Probability (HSP) and Recurrent Item Co-occurrence (RIC).
Book ChapterDOI
The Construction of Knowledge Graph for Personalized Online Teaching.
TL;DR: In this paper, a knowledge graph on python subject is constructed based on the neo4j graph database for students in programing courses and the experimental results show that the knowledge points to students are described more clearly, and the logical relationships between knowledge points are inferred according to the queries from students.
Proceedings ArticleDOI
Development of Cloud based Smart Voice Assistant using Amazon Web Services
TL;DR: In this paper , a web application called "Medico" is presented, which is a smart voice assistant with its applications in the medical sciences and it is an application created with Neo4j and AWS services connected.
Proceedings ArticleDOI
Categorization of the reviewers based on the preciseness of the consumers’ reviews in online retail marketplace
TL;DR: In this article , a novel methodology is suggested to classify reviewers into different categories based on the preciseness of the reviews, which can utilize the precise reviewers for getting genuine product feedback and encourage this group to promote their products.
Journal ArticleDOI
A Flexible Session-Based Recommender System for e-Commerce
Michail Salampasis,Alkiviadis Katsalis,Theodosios Siomos,Marina Delianidi,Dimitrios Tektonidis,Konstantinos Christantonis,Pantelis I. Kaplanoglou,Ifigeneia Karaveli,Chrysostomos Bourlis,Konstantinos I. Diamantaras +9 more
TL;DR: In this article , a large range of methods, from simpler statistical co-occurrence methods to embeddings and SotA deep learning methods, have been evaluated for session-based recommendation in e-commerce applications.
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