A User Behavior-Based Agent for Improving Web Usage

2002 ◽  
pp. 1168-1185 ◽  
Author(s):  
Francesco Buccafurri ◽  
Gianluca Lax ◽  
Domenico Rosaci ◽  
Domenico Ursino
Keyword(s):  
User Behavior ◽  
Web Usage ◽  
Behavior Based

SFIM: Identify user behavior based on stable features

2021 ◽  
Author(s):  
Hua Wu ◽  
Qiuyan Wu ◽  
Guang Cheng ◽  
Shuyi Guo ◽  
Xiaoyan Hu ◽  
...  
Keyword(s):  
User Behavior ◽  
Behavior Based

Research on Correlation Analysis of Power User Behavior Based on Coupled Meteorological Factors

2021 ◽  
Author(s):  
Yixiao Li ◽  
Tianguang Lv ◽  
Xin Zhao ◽  
Jiyan Liu ◽  
Wenjie Ju ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
User Behavior ◽  
Meteorological Factors ◽  
Behavior Based

Performance of User Behavior-Based Similarity on Top-N Recommendation

2021 ◽  
Author(s):  
Triyanna Widiyaningtyas ◽  
Indriana Hidayah ◽  
Teguh Bharata Adji
Keyword(s):  
User Behavior ◽  
Behavior Based

Web Usage Mining Issues in Big Data

2021 ◽  
pp. 102-112
Author(s):  
Sunny Sharma ◽  
Manisha Malhotra
Keyword(s):  
Data Mining ◽  
Big Data ◽  
User Behavior ◽  
Web Usage Mining ◽  
Web Personalization ◽  
Data Mining Techniques ◽  
Meaningful Information ◽  
Web Usage ◽  
Use Of Data ◽  
The Web

Web usage mining is the use of data mining techniques to analyze user behavior in order to better serve the needs of the user. This process of personalization uses a set of techniques and methods for discovering the linking structure of information on the web. The goal of web personalization is to improve the user experience by mining the meaningful information and presented the retrieved information in a way the user intends. The arrival of big data instigated novel issues to the personalization community. This chapter provides an overview of personalization, big data, and identifies challenges related to web personalization with respect to big data. It also presents some approaches and models to fill the gap between big data and web personalization. Further, this research brings additional opportunities to web personalization from the perspective of big data.

They Know What You Will Do Next Click

2020 ◽  
pp. 100-122
Author(s):  
Serra Çelik
Keyword(s):  
Focus Group ◽  
User Behavior ◽  
Web Usage Mining ◽  
Web Log ◽  
Web Usage ◽  
User Behaviors ◽  
Log Files ◽  
The Web

This chapter focuses on predicting web user behaviors. When web users enter a website, every move they make on that website is stored as web log files. Unlike the focus group or questionnaire, the log files reflect real user behavior. It can easily be said that having actual user behavior is a gold value for the organizations. In this chapter, the ways of extracting user patterns (user behavior) from the log files are sought. In this context, the web usage mining process is explained. Some web usage mining techniques are mentioned.

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