This document proposes a new approach to product recommendation systems for e-commerce websites. It discusses some limitations of current recommendation systems, such as being business motivated or only based on individual user interests. The proposed system aims to find similar users based on their ratings and dislikes to make recommendations. It also implements a verification step to only allow reviews from users who have purchased the product, to ensure reviews are genuine. The system would cluster users based on interests and notify further recommendations to users in the same cluster.
Product Quality Analysis based on online ReviewsIJSRD
Customers satisfaction is the most important criteria before buying any product. Technology today has grown to such an extent that every smallest possible query is found on internet. An individual can express his reviews towards a product through Internet. This allows others to have a brief idea about the product before buying one for them. In this paper, we take into account all the challenges and limitations encountered while reading the online reviews and time being consumed in understanding quality of the product from the reviews. We include several methods and algorithms that help the consumer to understand the Quality of the product in better way.
Product Quality Analysis based on online ReviewsIJSRD
Customers satisfaction is the most important criteria before buying any product. Technology today has grown to such an extent that every smallest possible query is found on internet. An individual can express his reviews towards a product through Internet. This allows others to have a brief idea about the product before buying one for them. In this paper, we take into account all the challenges and limitations encountered while reading the online reviews and time being consumed in understanding quality of the product from the reviews. We include several methods and algorithms that help the consumer to understand the Quality of the product in better way.
E-commerce online review for detecting influencing factors users perceptionjournalBEEI
To date, online shopping using e-commerce services becomes a trend. The emergence of e-commerce truly helps people to shop more effectively and efficiently. However, there are still some problems encountered in e-commerce, especially from the user perspective. This research aims to explore user review data, particularly on factors that influence user perception of e-commerce applications, classify, and identify potential solutions to finding problems in e-commerce applications. Data is grabbed using web scraping techniques and classified using proper machine learning, i.e., support vector machine (SVM). Text associations and fishbone analysis are performed based on the classified user review data. The results of this study show that the user satisfaction problem can be captured. Furthermore, various services that should be provided as a potential solution to experienced customers' problems or application users' perception problems can be generated. A detailed discussion of these findings is available in this article.
visit--- http://bit.ly/onlineshopping_javaproject For the complete project + CODE.
visit ------- javaprojects.tutoriallearners.in for other Java Projects
One Tap Publisher is typical of the evolution of traditional online advertising, typically distributed to the network by newspaper editors, television and radio stations. Historically, customers can rely on local newspaper, television and radio stations to find products and local products. With the development of the network, buyers are increasingly using search engines such as Google to find local products and services online
Most of us use e-shopping (Any product) these days and refer its rating or reviews before we download or buy that product. Amazon/Play store provide a great number of products but unfortunately few of those product reviews are fraud. Hence such products must be marked, so that they will be recognizable for rest of the users. Here we are comparing reviews from two sites so that we can get more clear idea. We can get higher probability of getting real reviews if we take data from multiple sites. We are proposing a system to develop an android application that will take reviews from two different websites for single product, and analyze them with NLP for positive or negative rating. In this, user will give two different URLs of two different sites for same product to the system as input. For every URL reviews and comments will be fetched separately and analyzed with NLP for positive negative rating. Then their rating will be combined together with average to give final rating for the product. As we are handling the big data here, we are using Hadoops map reduce. So it will be easier to decide which product reviews are fraud or not.
FOOD DELIVERY APP is a application designed primarily for use in the food delivery industry. This application will allow hotels, café, street food vendors and restaurants to increase scope of business by reducing the labor cost involved. Application presents an interactive and up-to-date menu with all available options in an easy to use manner. Customer can choose one or more items to place an order which will land in the cart before checking out. At the end customer can gets order confirmation details. Once the order is placed it is entered in the database and retrieved in pretty much real time.
Objective -
Develop a application that will allow customers to place their food order online and provide them with feedback, a generic image of the meal, a list of side dishes, main course ingredients, and cost information.
Product Quality Analysis based on online ReviewsIJSRD
Customers satisfaction is the most important criteria before buying any product. Technology today has grown to such an extent that every smallest possible query is found on internet. An individual can express his reviews towards a product through Internet. This allows others to have a brief idea about the product before buying one for them. In this paper, we take into account all the challenges and limitations encountered while reading the online reviews and time being consumed in understanding quality of the product from the reviews. We include several methods and algorithms that help the consumer to understand the Quality of the product in better way.
E-commerce online review for detecting influencing factors users perceptionjournalBEEI
To date, online shopping using e-commerce services becomes a trend. The emergence of e-commerce truly helps people to shop more effectively and efficiently. However, there are still some problems encountered in e-commerce, especially from the user perspective. This research aims to explore user review data, particularly on factors that influence user perception of e-commerce applications, classify, and identify potential solutions to finding problems in e-commerce applications. Data is grabbed using web scraping techniques and classified using proper machine learning, i.e., support vector machine (SVM). Text associations and fishbone analysis are performed based on the classified user review data. The results of this study show that the user satisfaction problem can be captured. Furthermore, various services that should be provided as a potential solution to experienced customers' problems or application users' perception problems can be generated. A detailed discussion of these findings is available in this article.
visit--- http://bit.ly/onlineshopping_javaproject For the complete project + CODE.
visit ------- javaprojects.tutoriallearners.in for other Java Projects
One Tap Publisher is typical of the evolution of traditional online advertising, typically distributed to the network by newspaper editors, television and radio stations. Historically, customers can rely on local newspaper, television and radio stations to find products and local products. With the development of the network, buyers are increasingly using search engines such as Google to find local products and services online
Most of us use e-shopping (Any product) these days and refer its rating or reviews before we download or buy that product. Amazon/Play store provide a great number of products but unfortunately few of those product reviews are fraud. Hence such products must be marked, so that they will be recognizable for rest of the users. Here we are comparing reviews from two sites so that we can get more clear idea. We can get higher probability of getting real reviews if we take data from multiple sites. We are proposing a system to develop an android application that will take reviews from two different websites for single product, and analyze them with NLP for positive or negative rating. In this, user will give two different URLs of two different sites for same product to the system as input. For every URL reviews and comments will be fetched separately and analyzed with NLP for positive negative rating. Then their rating will be combined together with average to give final rating for the product. As we are handling the big data here, we are using Hadoops map reduce. So it will be easier to decide which product reviews are fraud or not.
FOOD DELIVERY APP is a application designed primarily for use in the food delivery industry. This application will allow hotels, café, street food vendors and restaurants to increase scope of business by reducing the labor cost involved. Application presents an interactive and up-to-date menu with all available options in an easy to use manner. Customer can choose one or more items to place an order which will land in the cart before checking out. At the end customer can gets order confirmation details. Once the order is placed it is entered in the database and retrieved in pretty much real time.
Objective -
Develop a application that will allow customers to place their food order online and provide them with feedback, a generic image of the meal, a list of side dishes, main course ingredients, and cost information.
Product Quality Analysis based on online ReviewsIJSRD
Customers satisfaction is the most important criteria before buying any product. Technology today has grown to such an extent that every smallest possible query is found on internet. An individual can express his reviews towards a product through Internet. This allows others to have a brief idea about the product before buying one for them. In this paper, we take into account all the challenges and limitations encountered while reading the online reviews and time being consumed in understanding quality of the product from the reviews. We include several methods and algorithms that help the consumer to understand the Quality of the product in better way.
with current projections regarding the growth of
Internet sales, online retailing raises many questions about how
to market on the Net. A Recommender System (RS) is a
composition of software tools that provides valuable piece of
advice for items or services chosen by a user. Recommender
systems are currently useful in both the research and in the
commercial areas. Recommender systems are a means of
personalizing a site and a solution to the customer’s information
overload problem. Recommender Systems (RS) are software
tools and techniques providing suggestions for items and/or
services to be of use to a user. These systems are achieving
widespread success in ecommerce applications now a days, with
the advent of internet. This paper presents a categorical review
of the field of recommender systems and describes the state-ofthe-
art of the recommendation methods that are usually
classified into four categories: Content based Collaborative,
Demographic and Hybrid systems. To build our recommender
system we will use fuzzy logic and Markov chain algorithm.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.