scholarly journals A Survey Paper on: Frequent Pattern Analysis Algorithm from the Web Log Data

2015 ◽  
Vol 119 (13) ◽  
pp. 27-29 ◽  
Author(s):  
Samiksha Kankane ◽  
Vikram Garg
Keyword(s):  
Pattern Analysis ◽  
Frequent Pattern ◽  
Log Data ◽  
Analysis Algorithm ◽  
Web Log ◽  
Survey Paper ◽  
The Web

Markov Chain-Like Model for Prediction Service Based on Improved Hierarchical Particle Swarm Optimization Cluster Algorithm

2016 ◽  
Vol 26 (04) ◽  
pp. 653-674 ◽  
Author(s):  
Zhifang Liao ◽  
Min Liu ◽  
Tianhui Song ◽  
Li Kuang ◽  
Yan Zhang ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Markov Chain ◽  
Clustering Algorithms ◽  
Particle Swarm ◽  
Heterogeneous Data ◽  
Swarm Optimization ◽  
Log Data ◽  
Web Log ◽  
Proposed Model ◽  
The Web

Since web pages visited by users contain a variety of data resources and the clustering algorithms frequently used for web data do not take the heterogeneous nature into account when processing the heterogeneous data, this paper proposes a new algorithm, namely IHPSOC algorithm, to cluster web log data on the basis of web log mining. Based on particle swarm optimization (PSO), IHPSOC algorithm clusters the web log data through particle swarm iteration. Based on clustering results, this paper establishes Markov chain-like models which create a corresponding Markov chain for users in each different category so as to predict the web resources in users’ need. The results of the experiments show that the proposed model gives better predication.

scholarly journals Indexing Techniques for Web Access Logs

2004 ◽  
pp. 305-334 ◽  
Author(s):  
Yannis Manolopoulos ◽  
Mikolaj Morzy ◽  
Tadeusz Morzy ◽  
Alexandros Nanopoulos ◽  
Marek Wojciechowski ◽  
...  
Keyword(s):  
Log Data ◽  
Web Log ◽  
Indexing Techniques ◽  
Web Access ◽  
User Access ◽  
Single User ◽  
Efficient Processing ◽  
Access Logs ◽  
Web Access Logs ◽  
The Web

Access histories of users visiting a web server are automatically recorded in web access logs. Conceptually, the web-log data can be regarded as a collection of clients’ access-sequences, where each sequence is a list of pages accessed by a single user in a single session. This chapter presents novel indexing techniques that support efficient processing of so-called pattern queries, which consist of finding all access sequences that contain a given subsequence. Pattern queries are a key element of advanced analyses of web-log data, especially those concerning typical navigation schemes. In this chapter, we discuss the particularities of efficiently processing user access-sequences with pattern queries, compared to the case of searching unordered sets. Extensive experimental results are given, which examine a variety of factors and illustrate the superiority of the proposed methods over indexing techniques for unordered data adapted to access sequences.

scholarly journals An Appraisal on Recurrent Pattern Analysis Algorithm from the Net Monitor Records

2018 ◽  
Vol 7 (2.7) ◽  
pp. 542
Author(s):  
Sri Hari Nallamala ◽  
Siva Kumar Pathuri ◽  
Dr Suvarna Vani Koneru
Keyword(s):  
Data Mining ◽  
Data Structure ◽  
Web Mining ◽  
Pattern Analysis ◽  
Frequent Pattern ◽  
Analysis Algorithm ◽  
Additional Information ◽  
Internal Memory ◽  
Large Tree ◽  
Media Applications

Web data mining is a rising examination territory where taking out information is an essential job and a range of algorithms has been projected with a specific end goal to comprehend the an assortment of issues identified with web mining from available dataset. Here, we focus Frequent Pattern-Growth algorithm for data mining. Concerning FP-Growth, the efficiency is insufficient since mining progression is depends on large tree-frame data structure by internal memory estimate. We focuses on server monitor documents to find web convention forms of websites using web utilization mining and in exacting spotlights. Here, we had the practice to work with the projected strategy which could conceivable to eradicate the disadvantage of restriction of the presented rehearse in the area of web mining. An assortment of web usage mining practice can advance effort on numerous areas of scientific, medical & social media applications to advance toward for the research & security united zone. A briefed outline development system could help in gathering additional information on utilizing line up algorithm which shows the information state-plans effectually.  

scholarly journals Tracking User Interaction with Web and Assisting in Targeted Communication

2021 ◽  
Vol 9 (VI) ◽  
pp. 605-611
Author(s):  
Dheeraj Ahuja
Keyword(s):  
Social Media ◽  
Digital Technology ◽  
User Interaction ◽  
User Performance ◽  
Support Design ◽  
User Interactions ◽  
Log Data ◽  
Web Log ◽  
Log Files ◽  
The Web

Today, we spend most of our time online using some form of digital technology (such as search engines, news portals, or social media sites). Our online presence keeps us involved most of the time and provides a lot of information to Internet customers. The development of the web is excellent because every day about a million pages are added. Due to the massive use of the network, the log files of the network increase at a faster rate and the scope becomes enormous. Web Usage Mining uses mining technology on log data to extract user performance, which is used in different applications such as support design, e-commerce, service modification, prefetch, etc. In this paper, we propose a tool that users can use to collect data on their website, and then use this web log data to track user interactions on your website, which helps in targeted communication.

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