scholarly journals Application of CBIR in E-commerce

2020 ◽  
Vol 9 (2) ◽  
pp. 439-444
Keyword(s):  
Neural Network ◽  
Online Shopping ◽  
Content Based Image Retrieval ◽  
The Internet ◽  
Learning Method ◽  
Query Image ◽  
The World ◽  
Shopping Experience ◽  
Time Required ◽  
The Given

The rise of technology and the rapidly increasing inventions in Science have completely changed many aspects of the world today. Many sectors such as communication, banking, media, etc. have gained momentum because of the internet. Online shopping is one such sector that has flourished in recent times because of the internet. This paper presents a method which employs the system of Content Based Image Retrieval (CBIR) in online shopping. Using this system, the time required to shop online will be reduced. CBIR is the activity of fetching images from the database which have some similarity to the given query image. Traditionally customers would have to search from different categories and apply various filters to buy the product that they want. But in this system, they will be provided with an option to directly upload the image of the product that they wish to buy. If similar products are available, it will be displayed to the customer immediately. Thus, the time required for a customer to buy a product reduces considerably thereby making the shopping experience fun, easy and convenient. The system works in a way such that when an image is uploaded, the features of this image are extracted by using the deep learning method of Convolutional Neural Network (CNN). These extracted features are compared with the features of the available images stored in the database. Then, the similarity measure is calculated and images that are akin to the query image are found and are set out as result. This method significantly helps in reducing the time required to search for a particular product.

India Goes Digital..Smartphone is the New Shopping Destination

2018 ◽  
Vol 6 (8) ◽  
pp. 289
Author(s):  
Shankar Chaudhary
Keyword(s):  
Online Shopping ◽  
Mobile Apps ◽  
Smart Phone ◽  
Mobile Commerce ◽  
Mobile App ◽  
Smart Phones ◽  
The Internet ◽  
The World ◽  
Shopping Experience ◽  
User Friendly

Despite being in nascent stage m-commerce is gaining momentum in India. The explosive growth of smart-phone users has made India much loved business destination for whole world. Indian internet user is becoming the second largest in the world next to China surpassing US, which throws open plenty of e-commerce opportunities, not only for Indian players, offshore players as well. Mobile commerce is likely to overtake e-commerce in the next few years, spurred by the continued uptrend in online shopping and increasing use of mobile apps.The optimism comes from the fact that people accessing the Internet through their mobiles had jumped 33 per cent in 2014 to 173 million and is expected to grow 21 per cent year-on-year till 2019 to touch 457 million. e-Commerce brands are eyeing on the mobile app segment by developing user-friendly and secure mobile apps offering a risk-free and easy shopping experience to its users. Budget 4G smart phones coupled with affordable plans, can very well drive 4G growth in India.

Influence of Perceived Benefits on Consumers' Online Purchase Behaviour

2021 ◽  
pp. 1835-1863
Author(s):  
Rama Mohana Rao Katta ◽  
Chandra Sekhar Patro
Keyword(s):  
Online Shopping ◽  
The Internet ◽  
Perceived Benefits ◽  
Key Factors ◽  
Corporate Managers ◽  
Online Sales ◽  
Online Purchase ◽  
Factors Influencing ◽  
The World ◽  
Shopping Experience

This article describes how e-retailing has become one of the most important uses of technology relating to the internet. The activity of online shopping is considered to be one of the important features of e-retailing. The enormous advantages offered by online shopping stimulate corporate managers, marketing departments and retailers to offer their products through the websites to attract the largest number of shoppers, not only to local markets but also global markets. The change in consumer behavior along with the availability of cheaper and reliable technology for secure transactions has led to a significant growth in online sales around the world. The present article focuses on identifying the key factors influencing the consumers' perceived benefits while shopping online. The article further focuses on the influence of demographic factors on consumers' perceived benefits. The findings of the article would help e-retailers to have a better understanding and to develop strategies for making the online shopping experience more effective and trustworthy to the target consumers.

scholarly journals SWOT Analysis of Top Two Online Shopping Companies of India

2020 ◽  
pp. 144-146
Keyword(s):  
Swot Analysis ◽  
Online Shopping ◽  
The Internet ◽  
The World ◽  
Lengthy Process

The world of the Internet is so big that the more you learn about the Internet, the less. Due to Internet, our life has become a lot easier. You may not even think that today you can get the exam results online with the help of the Internet, connect with friends online, earn money online from the internet, and still do much more online. But nowadays the most popular is online shopping. Because of online shopping we can buy anything from home. And the same thing we bought comes to the address we have provided. We don't have to go anywhere. Online shopping is convenient, and consumers also have a wider range of choice. But people need to understand that no company or trader can afford to hurt you by giving you cheap or free. So instead of being tempted to buy from free and discount schemes, it is important to consider such websites and their 'non-refundable' policy and the complicated and lengthy process of returning items. Nowadays everyone recommends shopping online because of their busy and fast life. The more convenient it is, the more troubles can arise.

scholarly journals Customer Perception Towards Online Shopping in Chennai City

2019 ◽  
Vol 8 (4S3) ◽  
pp. 278-280
Keyword(s):  
Online Shopping ◽  
The Internet ◽  
Internet Shopping ◽  
Web Based ◽  
Effective Utilization ◽  
Customer Perception ◽  
The World ◽  
Online Stores ◽  
Chennai City ◽  
Number Of Individuals

Online based purchasing is the way toward buying products and enterprises from traders who sell them online through Internet. Since the rise of the World Wide Web, sellers have tried to offer their items to individuals who browser the Internet. Customers can visit online stores from their homes and shop comfortably. Presently a day shopping has turned out to be mainstream among individuals through browsing which has increased their web knowledge and effective utilization of internet. So internet shopping has become accustomed to the buyers which made the researcher to study the perception on internet based shopping. The principle aim of the this research is to find out the opinion of the respondents towards internet shopping. These days, there has been a flood in web based shopping. The Internet has been utilized by clothing organizations to sell their items and advance their brands. As an ever increasing number of individuals purchase attire on the web, there have been an expanding number of inquires about.

Machine Learning Approach for Content Based Image Retrieval

2012 ◽  
pp. 1-11 ◽  
Author(s):  
Siddhivinayak Kulkarni
Keyword(s):  
Neural Networks ◽  
Image Retrieval ◽  
Image Features ◽  
Content Based Image Retrieval ◽  
The Internet ◽  
Learning Approach ◽  
Query Image ◽  
Low Level ◽  
Machine Learning Approach ◽  
Efficient Retrieval

Developments in technology and the Internet have led to an increase in number of digital images and videos. Thousands of images are added to WWW every day. Content based Image Retrieval (CBIR) system typically consists of a query example image, given by the user as an input, from which low-level image features are extracted. These low level image features are used to find images in the database which are most similar to the query image and ranked according their similarity. This chapter evaluates various CBIR techniques based on fuzzy logic and neural networks and proposes a novel fuzzy approach to classify the colour images based on their content, to pose a query in terms of natural language and fuse the queries based on neural networks for fast and efficient retrieval. A number of experiments were conducted for classification, and retrieval of images on sets of images and promising results were obtained.

Deep Learning-Based Classification of Customers Towards Online Purchase Behaviour

2020 ◽  
Vol 10 (4) ◽  
pp. 74-86
Author(s):  
Juin Ghosh Sarkar ◽  
Tuhin Mukherjee ◽  
Isita Lahiri
Keyword(s):  
Neural Network ◽  
Technological Innovation ◽  
Online Shopping ◽  
Dynamic Environment ◽  
The Internet ◽  
Online Purchase ◽  
Daunting Task ◽  
Demographic Attributes ◽  
Internet Revolution

Online shopping is the new trend and is quickly becoming an integral part of our lifestyle. Due to the internet revolution and massive e-commerce usage by traders, online shopping has seen mammoth growth in recent years. In today's intensely competitive and dynamic environment with technological innovation in every sphere, knowing the consumer mind is the most daunting task for the success of any business. In this backdrop, the researchers have developed a neural network model. They have also made an attempt to classify the customers into two disjoint classes that are interested and uninterested online customers regarding purchase of home appliances through internet in and around Kolkata based on five demographic attributes, namely age, gender, place of residence, occupation, and income. The paper also focuses to optimise the parameters of the proposed neural network and test the efficiency of the constructed model and compare the result by reviewing the existing literatures on the related topic.

Big Data: A Very Short Introduction

2017 ◽  
Author(s):  
Dawn E. Holmes
Keyword(s):  
Social Media ◽  
Big Data ◽  
Online Shopping ◽  
The Internet ◽  
Gps Data ◽  
Security Risks ◽  
Short Introduction ◽  
Business World ◽  
The World ◽  
Diverse Cultures

Since long before computers were even thought of, data has been collected and organized by diverse cultures across the world. Once access to the Internet became a reality for large swathes of the world’s population, the amount of data generated each day became huge, and continues to grow exponentially. It includes all our uploaded documents, videos, and photos; all our social media traffic; our online shopping; even the GPS data from our cars. Big Data: A Very Short Introduction explains how big data works and is changing the world around us, the effect it has on our everyday lives and in the business world, and it considers the attendant security risks.

scholarly journals Recent innovations in Distributed Systems: Challenges and Benefits

2013 ◽  
Vol 10 (10) ◽  
pp. 2057-2061
Author(s):  
Madhurima Hooda ◽  
Amandeep Kaur ◽  
Madhulika Bhadauria
Keyword(s):  
Distributed Systems ◽  
Distributed System ◽  
World Wide ◽  
Online Shopping ◽  
The Internet ◽  
Web Browser ◽  
The World ◽  
Access Information ◽  
Mobile Computers ◽  
The Web

The World Wide Web is used by millions of people everyday for various purposes including email, reading news, downloading music, online shopping or simply accessing information about anything. Using a standard web browser, the user can access information stored on Web servers situated anywhere on the globe. This gives the illusion that all this information is situated locally on the user’s computer. In reality, the Web represents a huge distributed system that appears as a single resource to the user available at the click of a button. This paper gives an overview of distributed systems in current IT sector. Distributed systems are everywhere. The internet enable users throughout the world to access its services wherever they may be located [1]. Each organization manages an intranet, which provides local services for local users and generally provides services to other users in the internet. Small distributed systems can be constructed from mobile computers and other small computational devices that are attached to a wireless network.

scholarly journals Content Based Image Retrieval using Multi-level 3D Color Texture and Low Level Color Features with Neural Network Based Classification System

2021 ◽  
Vol 15 ◽  
pp. 265-270
Author(s):  
Priyesh Tiwari ◽  
Shivendra Nath Sharan ◽  
Kulwant Singh ◽  
Suraj Kamya
Keyword(s):  
Neural Network ◽  
Image Retrieval ◽  
Texture Feature ◽  
Texture Features ◽  
Classification Model ◽  
Content Based Image Retrieval ◽  
Query Image ◽  
Multi Level ◽  
Different Color ◽  
Color Texture

Content based image retrieval (CBIR), is an application of real-world computer vision domain where from a query image, similar images are searched from the database. The research presented in this paper aims to find out best features and classification model for optimum results for CBIR system.Five different set of feature combinations in two different color domains (i.e., RGB & HSV) are compared and evaluated using Neural Network Classifier, where best results obtained are 88.2% in terms of classifier accuracy. Color moments feature used comprises of: Mean, Standard Deviation,Kurtosis and Skewness. Histogram features is calculated via 10 probability bins. Wang-1k dataset is used to evaluate the CBIR system performance for image retrieval.Research concludes that integrated multi-level 3D color-texture feature yields most accurate results and also performs better in comparison to individually computed color and texture features.

scholarly journals A Novel Multi Hidden Layer Convolutional Neural Network for Content Based Image Retrieval

2020 ◽  
Vol 9 (3) ◽  
pp. 365-370
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Image Retrieval ◽  
Convolutional Neural Network ◽  
Network Architecture ◽  
Learning Algorithm ◽  
Machine Learning Algorithms ◽  
Content Based Image Retrieval ◽  
Neural Network Architecture ◽  
Query Image

The applications of a content-based image retrieval system in fields such as multimedia, security, medicine, and entertainment, have been implemented on a huge real-time database by using a convolutional neural network architecture. In general, thus far, content-based image retrieval systems have been implemented with machine learning algorithms. A machine learning algorithm is applicable to a limited database because of the few feature extraction hidden layers between the input and the output layers. The proposed convolutional neural network architecture was successfully implemented using 128 convolutional layers, pooling layers, rectifier linear unit (ReLu), and fully connected layers. A convolutional neural network architecture yields better results of its ability to extract features from an image. The Euclidean distance metric is used for calculating the similarity between the query image and the database images. It is implemented using the COREL database. The proposed system is successfully evaluated using precision, recall, and F-score. The performance of the proposed method is evaluated using the precision and recall.

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