scholarly journals Product recommendation system based user purchase criteria and product reviews

2019 ◽  
Vol 9 (6) ◽  
pp. 5454
Author(s):  
Jinyoung Kim ◽  
Doyeun Hwang ◽  
Hoekyung Jung
Keyword(s):  
Morphological Analysis ◽  
Recommendation System ◽  
Product Evaluation ◽  
Shopping Mall ◽  
Product Reviews ◽  
Purchasing Decisions ◽  
Product Review ◽  
Product Recommendation ◽  
Average Value ◽  
Purchase Criteria

<span lang="EN-US">In this paper, we propose a system that provides customized product recommendation information after crawling product review data of internet shopping mall with unstructured </span><span lang="EN-US">data</span><span lang="EN-US">, morphological analysis using Python. User searches for a proudct to be purchased and select the most important purchase criteria when purchasing the product. User searches for a proudct to be purchased and select the most important purchase criteria when purchasing the product.</span><span lang="EN-US"> And extracts and analyzes only the review including the purchase criterion selected by the user among the product reviews left by other users. The positive and negative evaluations contained in the extracted product review data are quantified and using the average value, we extract the top 10 products with good product evaluation, sort and recommend to users. And provides user-customized information that reflects the user's preference by arranging and providing a center around the criteria that the user occupies the largest portion of the product purchase. This allows users to reduce the time it takes to purchase a product and make more efficient purchasing decisions.</span>

scholarly journals Personal customized recommendation system reflecting purchase criteria and product reviews sentiment analysis

2021 ◽  
Vol 11 (3) ◽  
pp. 2399
Author(s):  
Wu Guanchen ◽  
Minkyu Kim ◽  
Hoekyung Jung
Keyword(s):  
Sentiment Analysis ◽  
Recommendation System ◽  
Business Environment ◽  
Product Reviews ◽  
Product Review ◽  
Recommendation Algorithm ◽  
Purchase Criteria ◽  
Sentiment Score ◽  
A Company

As the size of the e-commerce market grows, the consequences of it are appearing throughout society. The business environment of a company changes from a product center to a user center and introduces a recommendation system. However, the existing research has shown a limitation in deriving customized recommendation information to reflect the detailed information that users consider when purchasing a product. Therefore, the proposed system reflects the user's subjective purchasing criteria in the recommendation algorithm. And conduct sentiment analysis of product review data. Finally, the final sentiment score is weighted according to the purchase criteria priority, recommends the results to the user.

Hybrid Collaborative Fusion Based Product Recommendation Exploiting Sentiments from Implicit and Explicit Reviews

2021 ◽  
pp. 2141013
Author(s):  
N Zafar Ali Khan ◽  
R. Mahalakshmi
Keyword(s):  
Recommendation System ◽  
Recommendation Systems ◽  
User Profile ◽  
Personalized Recommendation ◽  
Product Reviews ◽  
Aspect Mining ◽  
Product Recommendation ◽  
Collaborative Recommendation ◽  
Demographic Attributes ◽  
Implicit And Explicit

Product recommendation is an important functionality in online ecommerce systems. The goal of the recommendation system is to recommend products with has higher purchase success ratio. User profile, product purchase history etc. have been used in many works to provide high quality recommendations. Product reviews is one of the important source for personalized recommendation. Typical collaborative recommendation systems are built upon user rating on products. But in many cases, these rating information are inaccurate or not available. There is also a problem of biased reviews decreasing the accuracy of recommendation systems. This work proposes a aspect mining collaborative fusion based recommendation system considering both the implicit and explicit reviews. The sentiments about different aspects mined from reviews are translated to multi-dimensional ratings. These ratings are then fused with user profile and demographic attributes to improve the quality of recommendation. The proposed recommendation system has 3.79% lower RMSE, 4.51% lower MAE and 22% lower MRE compared to most recent collaborative filtering based recommendation system.

Online Product Recommendation System by Using Eye Gaze Data

2020 ◽  
Author(s):  
A. B. M. Fahim Shahriar ◽  
Mahedee Zaman Moon ◽  
Hasan Mahmud ◽  
Kamrul Hasan
Keyword(s):  
Recommendation System ◽  
Eye Gaze ◽  
Product Recommendation

scholarly journals Product Recommendation System a Comprehensive Review

2021 ◽  
Vol 1022 ◽  
pp. 012021
Author(s):  
Jatin Sharma ◽  
Kartikay Sharma ◽  
Kaustubh Garg ◽  
Avinash Kumar Sharma
Keyword(s):  
Recommendation System ◽  
Comprehensive Review ◽  
Product Recommendation ◽  
System A

The Influence of Marketing Mix Variables on Purchasing Decisions and Its Impact on Post-Purchase Customer Satisfaction of Royal Garden Residence Bali Housing (Study at PT Properti Bali Benoa)

2021 ◽  
Vol 4 (1) ◽  
pp. 157-172
Author(s):  
Edi Sugiono ◽  
Andini Nurwulandari ◽  
Christiani Junita
Keyword(s):  
Customer Satisfaction ◽  
Marketing Mix ◽  
Purchase Decisions ◽  
Purchasing Decisions ◽  
Online Questionnaire ◽  
Product Price ◽  
Average Value ◽  
Decision Variables ◽  
Post Purchase ◽  
The City

A B S T R A C TThe research objective is to determine the effect of: marketing mix variables(product, price, location and promotion) on purchasing decision variables,marketing mix variables on customer satisfaction variables, purchasing decisionvariables on customer satisfaction variables at Royal Garden Residence Balihousing with purchase decisions as a mediating variable. . This research wasconducted in the city of Bali, with the object of research being the residentialconsumers of Royal Garden Residence Bali as the population in this study, with asample size of 150 respondents and using random sampling techniques. The datacollection method is in the form of an online questionnaire via google form andwhatsaap due to the situation in Indonesia which is currently being hit by theCovid-19 pandemic. The results of this study indicate that respondents have a goodperception of the variable marketing mix, purchase decisions and post-purchasesatisfaction Royal Garden Residence Bali. This is because the average value for allresearch variables is greater than 4 on the Likert scale. The results showed that themarketing mix variable both simultaneously and partially had a positive andsignificant effect on housing purchase decisions and the marketing mix variablehad a positive and significant effect both simultaneously and partially on consumersatisfaction after purchasing Royal Garden Residence Bali housing, and purchasingdecisions had a positive and significant effect. significant on consumer satisfactionafter purchasing the Royal Garden Residence Bali housing. Then the research alsoproves that there is an indirect influence of the marketing mix variable on consumersatisfaction after purchasing the Royal Garden Residence Bali housing through thepurchase decision. Promotion is the most dominant variable in increasingconsumer purchasing decisions for Royal Garden Residence Bali housing.

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