scholarly journals Smart Cart with Automatic Billing, Product Information, Product Recommendation Using RFID & Zigbee with Anti-Theft

2016 ◽  
Vol 79 ◽  
pp. 793-800 ◽  
Author(s):  
Ankush Yewatkar ◽  
Faiz Inamdar ◽  
Raj Singh ◽  
Ayushya ◽  
Amol Bandal
Keyword(s):  
Product Information ◽  
Information Product ◽  
Product Recommendation

scholarly journals Product Recommendation Agents for Cyber Shopping Consumers

2012 ◽  
pp. 586-599
Author(s):  
Tobias Kowatsch ◽  
Wolfgang Maass
Keyword(s):  
Dynamic Pricing ◽  
Product Information ◽  
Consumer Electronics ◽  
Future Research ◽  
Purchase Decision ◽  
Product Reviews ◽  
Product Recommendation ◽  
Future Research Directions ◽  
Recommendation Agents ◽  
Product Recommendation Agents

With cyber shopping, consumers face a massive amount of product information before an educated purchase decision can be made. Identifying relevant products is therefore laborious for consumers, in particular when they look for non-commodity products such as consumer electronics. Product Recommendation Agents (PRAs) help consumers in finding relevant products efficiently. PRAs recommend a set of products either explicitly according to product attributes preferred by the consumer or implicitly based on consumers’ interests and activities. PRAs retrieve hereby product information from various sources such as a retailer’s product database or a third-party’s review database. This entry introduces and discusses PRAs for cyber shopping consumers from five perspectives: (1) Purchase decision-making, (2) natural language interaction, (3) dynamic pricing, (4) product reviews, and finally, (5) product recommendation infrastructures. Future research directions on PRAs for cyber shopping conclude this entry.

scholarly journals Product Recommendation Based on Eye Tracking Data Using Fixation Duration

2021 ◽  
Vol 5 (4) ◽  
pp. 109
Author(s):  
Juni Nurma Sari ◽  
Lukito Edi Nugroho ◽  
Paulus Insap Santosa ◽  
Ridi Ferdiana
Keyword(s):  
Eye Tracking ◽  
Collaborative Filtering ◽  
Fixation Duration ◽  
Product Information ◽  
Sensor Technology ◽  
Tracking Data ◽  
Eye Tracker ◽  
Product Recommendation ◽  
User Attention ◽  
Product Recommendations

E-commerce can be used to increase companies or sellers’ profits. For consumers, e-commerce can help them shop faster. The weakness of e-commerce is that there is too much product information presented in the catalog which in turn makes consumers confused. The solution is by providing product recommendations. As the development of sensor technology, eye tracker can capture user attention when shopping. The user attention was used as data of consumer interest in the product in the form of fixation duration following the Bojko taxonomy. The fixation duration data was processed into product purchase prediction data to know consumers’ desire to buy the products by using Chandon method. Both data could be used as variables to make product recommendations based on eye tracking data. The implementation of the product recommendations based on eye tracking data was an eye tracking experiment at selvahouse.com which sells hijab and women modest wear. The result was a list of products that have similarities to other products. The product recommendation method used was item-to-item collaborative filtering. The novelty of this research is the use of eye tracking data, namely the fixation duration and product purchase prediction data as variables for product recommendations. Product recommendation that produced by eye tracking data can be solution of product recommendation’s problems, namely sparsity and cold start.

City Electronics Furniture Store System Order Based on ASP.NET

2014 ◽  
Vol 1044-1045 ◽  
pp. 1106-1109
Author(s):  
Yan Yan Cheng ◽  
Quan Bo Yuan
Keyword(s):  
Information Management ◽  
Product Information ◽  
Product Reviews ◽  
Order Information ◽  
Information Product ◽  
Tier System ◽  
System Project ◽  
System Order

The system uses B/S architecture, developed using ASP.NET electronic mall three-tier system. Project is divided into foreground and background, foreground realized commodity purchase and purchase orders, mainly for administrators to manage the background of product information, product reviews, order information management. After testing, the system completes the established function works well.

scholarly journals Increase Robustness SDAE with Imputing Missing Value To Eliminate Users Sparse Data in Case E-Commerce Recommender System

2018 ◽  
Vol 7 (4.44) ◽  
pp. 137
Author(s):  
Hanafi . ◽  
Nanna Suryana ◽  
Abd Samad Hasan Basari
Keyword(s):  
Collaborative Filtering ◽  
Recommender System ◽  
Evaluation Method ◽  
Product Information ◽  
Relevant Information ◽  
Sparse Data ◽  
Extreme Condition ◽  
Missing Value ◽  
Product Recommendation ◽  
Customer Profiling

Online shopping needs a computer machine to serve product information sale for customer or buyer candidate. Relevant information served by ecommerce system famous called recommender system. The successful to applied, it will have impact to increase of marketing target achievement. The character of information served by recommender system have to be special, personalized, relevant and fit according customer profiling. There are four kind of recommender system model, however there is one model that was successful to be applied in real ecommerce industry that popular named collaborative filtering. Collaborative filtering approach need a record users or customers activity in the past to generate recommendation for example rating record, purchasing record, testimony about product.  The majority collaborative filtering approaches rely on rating as fundamental computation to calculate product recommendation. However, just a little number of consumers who willing give rating for products less than a percent, according to several convince datasets such MovieLens. This problem causes of sparse product rating that will impact to product recommendation accuracy level. Sometime, in extreme condition, it is impossible to generate product recommendation. Several efforts have been conducting to handle product sparse rating, however they fail to generate product recommendation accurately when face extreme sparse data, such as matrix factorization family include SVD, NMF, SVD++. This research aims to develop a model to handle users sparse rating involving deep SDAE. One of the efforts to produce better output in handling this data sparse, our strategy is to imputing missing value by statistical method so that the input in SDAE is closer to the feasibility of data that is not too sparse. According to our experiment involve deep learning, TensorFlow, MovieLens datasets, evaluation method by root mean square error (RMSE), our approach involves reducing input missing value could address users sparse rating and increase robustness over several existing approach.  

Attitudes of E-Shoppers and Non E-Shoppers towards E-Shopping

2016 ◽  
Vol 6 (2) ◽  
pp. 96-108 ◽  
Author(s):  
Chandra Sekhar Patro
Keyword(s):  
Customer Service ◽  
Product Information ◽  
Daily Life ◽  
Information Product ◽  
Online Security ◽  
Factors Influencing ◽  
Competitive Prices ◽  
Current Scenario ◽  
Product Delivery ◽  
Practical Implications

Today, the emergence and rapid growth of E-commerce has triggered off many changes in daily life. This new phenomenon has promised change, challenges and even bright future, not only to consumers but also to the e-tailing companies, suppliers and middlemen. E-shopping plays a major role in the Indian economy and is expected to change the current scenario of shopping from physical stores to e-stores. This study aims to examine the buyers' attitude towards e-shopping and also to find the critical reasons for not shopping through online. The results reveal that buyers are still hesitating to shop online. The most important reasons for buyers in both cities not to shop online are online security, prefer to buy by touching and feeling, and customer service. The factors influencing to buy online are being able to get detailed product information, product delivery, convenience, product quality and competitive prices. These results also have some practical implications for managers and strategists of e-stores.

scholarly journals DOCUMENTARY FUND AS A REFLECTION LEVEL OF INFORMATION CULTURE OF THE LIBRARY

2021 ◽  
Author(s):  
Yuriy Paleкha ◽  
Natalya Kobyzhcha
Keyword(s):  
Information Retrieval ◽  
Corporate Culture ◽  
Information Technologies ◽  
Product Information ◽  
Digital Age ◽  
Source Information ◽  
Information Culture ◽  
Joint Work ◽  
Information Product ◽  
New Vision

The purpose of the article is to define the essence of the informational culture of the library, that represents the created documentary fund as an information product that is the result of the joint efforts of the staff, including its modeling, composition, and organization; to identify key elements and analyze components; outline directions for further research in terms of meeting the needs of the information society in the digital age. The methodology is to apply a culturological and systematic approach, general scientific methods of cognition, and the method of moving from the abstract to specific aspects. The scientific novelty of the work is to study the informational culture of the library and its documentary fund as a consolidated information product of joint efforts of its staff, which serves as an indicator of the level of the corporate culture of the library on the one hand and the informational culture of society on the other. The factors due to which the modern head of the library should take care of the informational culture of his institution, the main features and levels of the informational culture of the modern library are elaborated. Conclusions. The documentary fund as a product of joint activity and the main object of cultural creativity of the library staff can be presented as a complex, multidimensional structure, including the ability to collect and analyze source information, the ability to create electronic databases, knowledge of information retrieval systems and information retrieval techniques, ability to process information, skills of structuring documented information, knowledge of methods of preparation of different information documents, ability to provide information services. The combination of the main elements of the informational culture of the library is based on the principles of complexity, differential approach, and continuity and gives a new vision and understanding of the need for joint work on the formation of its documentary fund. The information culture of the library requires further research and detailed analysis of its components. Key words: informational culture; documentary fund; joint information product; information technologies; digital age.

Small Business Management Information System Design and Implementation

2014 ◽  
Vol 926-930 ◽  
pp. 3962-3965
Author(s):  
Li Juan Wang
Keyword(s):  
Modular Design ◽  
Product Information ◽  
Business Management ◽  
Information Management System ◽  
Enterprise Information ◽  
Application System ◽  
Information System Design ◽  
Information Product ◽  
Customer Information ◽  
Small Business Management

Abstract. This paper presents a model of C/S based database application system --enterprise information Management system. System uses a modular design, user information, customer information, product information, Inventory information detailed records, and convenient, fast query of the required information, to provide a strong guarantee for the enterprise production and sales, improve work efficiency and enterprise benefit.

No Idle Boast: Consumer Responses to Self-Enhancing Sources of Product Information

2014 ◽  
Author(s):  
Grant Packard ◽  
Andrew D. Gershoff ◽  
David B. Wooten
Keyword(s):  
Product Information ◽  
Consumer Responses
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