A survey on impact of data analytics techniques in E-commerce

In this paper, we present an approach for mining change in customer’s behavior for the purpose of maintaining robust profiling model over time. Most of previous studies leave important questions unanswered: In developing B2C e-commerce strategies, how do managers implicitly load customer’s profiles based on their satisfaction over the online store characteristics? And: What kind of feedback segments do they have? Our proposed approach does not force customers to explicitly express their preference information over the online service but rather capture their preference from their online activities. The challenge does not only lay in analyzing how customer’s classifier model change and when it does so but also to adapt it to the customer’s click stream data using a new decision tree generation algorithm which takes as inputs new set of variables; categorical, continuous and fuzzy variables. Customer’s online reviews rates are considered as classes. Experiments show that this work performed well in identifying relevant customer’s stream data to judge the chinese e-commerce website “Tmall”. The extracted values of the website’s features are also useful to identifying the satisfaction level when the customer’s rate is not available.

/pdf/a-novel-approach-to-dynamic-profiling-of-e-customers-4xwgk8hxzb.pdf

A novel approach to dynamic profiling of e-customers considering click stream data and online reviews

This research is the addition to the steps of making online business more user-friendly, interactive and output-oriented. The online marketing and sales of the products increase significantly if the opinion of the public for the product is analyzed intermittently. As the trend in today’s date is that people update their response to the products faced by them in day-to-day life immediately in the social media, the developed system provides the platform for the large-scale producers to inspect how the consumers are responding to their products. The concept of Big Data Analysis is used for data collection, pre-processing and data analysis. A model is obtained by training the available Data using Deep Learning, which is used for the determination of sentiment values of the collected comments. Finally, the python libraries are used for the visualization of the results of Sentiment analysis and other obtained information.

Big Data Analytics and Deep Learning Based Sentiment Analysis System for Sales Prediction

Technological developments in recent time of globalization, especially computer-based communication and information technology, where technology is the mainstay and needs of the world community are highly important. This is due to the very rapid development in the field of telecommunications and computers, which has pushed the world community into a fast-paced reform era, even though it has made information central in the industrial and business.

The Use of E-Commerce Website in MSME Product Marketing in Bengkulu Province

In general website evaluation includes website function and website content and website credit, customer service and enterprise strength, website security, its interface design and website technology. These studies mainly are based on evaluation approach on traditional websites. The arrival of the era of big data provides new opportunities and challenges to the construction and application of electronic commerce website. This paper analyzes the evaluation index of E - commerce website and introduce the evaluation method of e-commerce website, especially the construction of website with big data.

Research on the Evaluation of E-Commerce Website under the Environment of Big Data

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Pingping Dong

Author Tools

Chat about Author

Papers

Research on the Evaluation of E-Commerce Website under the Environment of Big Data