scholarly journals Application and Research of E-commerce Recommendation System Based on Web Mining

2016 ◽  
Author(s):  
Xu Yan ◽  
Bo Sun
Keyword(s):  
Web Mining ◽  
Recommendation System

A Movie E-Shop Recommendation Model Based on Web Usage and Ontological Data

2011 ◽  
pp. 51-68
Author(s):  
Andreas Aresti ◽  
Penelope Markellou ◽  
Ioanna Mousourouli ◽  
Spiros Sirmakessis ◽  
Athanasios Tsakalidis
Keyword(s):  
Artificial Intelligence ◽  
User Modeling ◽  
Web Mining ◽  
Recommendation System ◽  
Recommendation Systems ◽  
Model Based ◽  
Web Usage ◽  
One To One ◽  
Online Shops

Recommendation systems are special personalization tools that help users to find interesting information and services in complex online shops. Even though today’s e-commerce environments have drastically evolved and now incorporate techniques from other domains and application areas such as Web mining, semantics, artificial intelligence, user modeling, and profiling setting up a successful recommendation system is not a trivial or straightforward task. This chapter argues that by monitoring, analyzing, and understanding the behavior of customers, their demographics, opinions, preferences, and history, as well as taking into consideration the specific e-shop ontology and by applying Web mining techniques, the effectiveness of produced recommendations can be significantly improved. In this way, the e-shop may upgrade users’ interaction, increase its usability, convert users to buyers, retain current customers, and establish long-term and loyal one-to-one relationships.

DSS for Web Mining Using Recommendation System

2017 ◽  
pp. 22-34 ◽  
Author(s):  
Varaprasad Rao M ◽  
Vishnu Murthy G
Keyword(s):  
Recommender Systems ◽  
Web Mining ◽  
Recommendation System ◽  
User Behavior ◽  
Web Content ◽  
Web Structure ◽  
Web Structure Mining ◽  
Content Mining ◽  
Computer Based ◽  
The Many

Decision Supports Systems (DSS) are computer-based information systems designed to help managers to select one of the many alternative solutions to a problem. A DSS is an interactive computer based information system with an organized collection of models, people, procedures, software, databases, telecommunication, and devices, which helps decision makers to solve unstructured or semi-structured business problems. Web mining is the application of data mining techniques to discover patterns from the World Wide Web. Web mining can be divided into three different types – Web usage mining, Web content mining and Web structure mining. Recommender systems (RS) aim to capture the user behavior by suggesting/recommending users with relevant items or services that they find interesting in. Recommender systems have gained prominence in the field of information technology, e-commerce, etc., by inferring personalized recommendations by effectively pruning from a universal set of choices that directed users to identify content of interest.

Research and Application of Apriori Algorithm for Mining Association Rules

2014 ◽  
Vol 1079-1080 ◽  
pp. 737-742
Author(s):  
Yi Yong Ye
Keyword(s):  
Association Analysis ◽  
Association Rules ◽  
Web Mining ◽  
Recommendation System ◽  
Apriori Algorithm ◽  
Mining Algorithm ◽  
Common Technique ◽  
Mining Association Rules

For large amounts of data generated by the e-commerceplatform, combining with the actual needs of e-commerce recommendation system,make research on a common technique of association rules which orientede-commerce Web mining association analysis, introduces the association rules ofApriori mining algorithm, and the specific application of Apriori algorithm isanalyzed through a practical example, Finally, point out the shortcomings ofclassical Apriori algorithm, and gives directions for improvement.

BUILDING A KNOWLEDGE BASE FOR IMPLEMENTING A WEB-BASED COMPUTERIZED RECOMMENDATION SYSTEM

2007 ◽  
Vol 16 (05) ◽  
pp. 793-828 ◽  
Author(s):  
JUAN D. VELÁSQUEZ ◽  
VASILE PALADE
Keyword(s):  
Knowledge Base ◽  
Web Site ◽  
Web Mining ◽  
Recommendation System ◽  
The Internet ◽  
Web Pages ◽  
Web Based ◽  
Web Logs ◽  
Mining Tools ◽  
The Web

Understanding the web user browsing behaviour in order to adapt a web site to the needs of a particular user represents a key issue for many commercial companies that do their business over the Internet. This paper presents the implementation of a Knowledge Base (KB) for building web-based computerized recommender systems. The Knowledge Base consists of a Pattern Repository that contains patterns extracted from web logs and web pages, by applying various web mining tools, and a Rule Repository containing rules that describe the use of discovered patterns for building navigation or web site modification recommendations. The paper also focuses on testing the effectiveness of the proposed online and offline recommendations. An ample real-world experiment is carried out on a web site of a bank.

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