The document discusses using machine learning techniques like text mining and natural language processing to analyze customer feedback from online reviews in order to identify frequently reported product and service issues and provide statistical reports to help businesses improve quality. It reviews previous research on sentiment analysis and text classification methods for product review data and proposes a methodology that includes crawling reviews, preprocessing text, building a classifier to predict labels, and generating statistical reports.
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.
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.
In this paper, the combined charge difficulty evaluation and testees level for intellect appraisal are to find the
employee performance. In testing the tests and task evaluation of different designation employee’s
performance outcome result is difficult to rank the outcome result. Whereby higher officials evaluate and
provide feedback on employee job performance, including steps to improve or redirect activities as need.
Higher official documenting performance provides a basis for pay increases and promotions. In this project,
higher official evaluates the lower official by assigning task and testees. The higher official will solve the
difficulties of testing and ranking problem for appraisal. All these findings are useful to intelligence tests. Here
the evaluation of each employee was calculated and view by the Bernoulli’s Distribution algorithm.
Task evaluation, employee appraisal, ranking of employees
ASPECT-BASED OPINION EXTRACTION FROM CUSTOMER REVIEWScsandit
Text is the main method of communicating information in the digital age. Messages, blogs,
news articles, reviews, and opinionated information abounds on the Internet. People commonly
purchase products online and post their opinions about purchased items. This feedback is
displayed publicly to assist others with their purchasing decisions, creating the need for a
mechanism with which to extract and summarize useful information for enhancing the decisionmaking
process. Our contribution is to improve the accuracy of extraction by combining
different techniques from three major areas, namedData Mining, Natural Language Processing
techniques and Ontologies. The proposed framework sequentially mines product’s aspects and
users’ opinions, groups representative aspects by similarity, and generates an output summary.
This paper focuses on the task of extracting product aspects and users’ opinions by extracting
all possible aspects and opinions from reviews using natural language, ontology, and frequent
“tag”sets. The proposed framework, when compared with an existing baseline model, yielded
promising results.
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.
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.
In this paper, the combined charge difficulty evaluation and testees level for intellect appraisal are to find the
employee performance. In testing the tests and task evaluation of different designation employee’s
performance outcome result is difficult to rank the outcome result. Whereby higher officials evaluate and
provide feedback on employee job performance, including steps to improve or redirect activities as need.
Higher official documenting performance provides a basis for pay increases and promotions. In this project,
higher official evaluates the lower official by assigning task and testees. The higher official will solve the
difficulties of testing and ranking problem for appraisal. All these findings are useful to intelligence tests. Here
the evaluation of each employee was calculated and view by the Bernoulli’s Distribution algorithm.
Task evaluation, employee appraisal, ranking of employees
ASPECT-BASED OPINION EXTRACTION FROM CUSTOMER REVIEWScsandit
Text is the main method of communicating information in the digital age. Messages, blogs,
news articles, reviews, and opinionated information abounds on the Internet. People commonly
purchase products online and post their opinions about purchased items. This feedback is
displayed publicly to assist others with their purchasing decisions, creating the need for a
mechanism with which to extract and summarize useful information for enhancing the decisionmaking
process. Our contribution is to improve the accuracy of extraction by combining
different techniques from three major areas, namedData Mining, Natural Language Processing
techniques and Ontologies. The proposed framework sequentially mines product’s aspects and
users’ opinions, groups representative aspects by similarity, and generates an output summary.
This paper focuses on the task of extracting product aspects and users’ opinions by extracting
all possible aspects and opinions from reviews using natural language, ontology, and frequent
“tag”sets. The proposed framework, when compared with an existing baseline model, yielded
promising results.
PRODUCT REPUTATION AND GLOBAL RATING IN E-COMMERCE IAEME Publication
Trust is an important factor for E-commerce and has been an issue for the peopleusing E-Commerce for their habitual shopping purpose, whereas E-Commerce is verymuch money saving as compared to traditional offline shopping. But peoplefear using
E-Commerce just because there is no contingence with the seller. So it is a hugechallenge to isolate this fear from the mindset of buyers. The only alternative to isolatethis fear is coming up with a reliable trust in their minds. There are many conditions
which should be taken care of depending upon which our trustwhich includes past history, reputation, websitequality, and seller's response and customer support.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
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.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
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/
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.
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.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.