Analyzing and Predicting User Navigation Pattern from Weblogs using Modified Classification Algorithm
نویسندگان
چکیده
منابع مشابه
Analyzing the User Navigation Pattern from Weblogs Using Data Pre-processing Technique
In the real world, lot of users attracted towards online shopping, so lots of transactions are going on in the websites. A weblog contains series of entries updating frequently by the user while accessing the website. Based on the user interest, it can be classified as related and unrelated data. The related data can be considered as success response, but the unrelated data can be considered as...
متن کاملUser-Driven Navigation Pattern Discovery from Internet Data
Managers of electronic commerce sites need to learn as much as possible about their customers and those browsing their virtual premises, in order to maximise the return on marketing expenditure. The discovery of marketing related navigation patterns requires the development of data mining algorithms capable of the discovery of sequential access patterns from web logs. This paper introduces a ne...
متن کاملPredicting Social Networks in Weblogs
Weblogs and other platforms used to organize a social life online have achieved an enormous success over the last few years. Opposed to applications directly designed for building up and visualizing social networks, weblogs are comprised of mostly unstructured text data, that comes with some meta data, such as the author of the text, its publication date or the URL it is available under. In thi...
متن کاملSimultaneous Pattern and Data Clustering Using Modified K-Means Algorithm
In data mining and knowledge discovery, for finding the significant correlation among events Pattern discovery (PD) is used. PD typically produces an overwhelming number of patterns. Since there are too many patterns, it is difficult to use them to further explore or analyze the data. To address the problems in Pattern Discovery, a new method that simultaneously clusters the discovered patterns...
متن کاملGenetic Algorithm based Rule Extraction from Pruned Modified Fuzzy Hyperline Segment Neural Network for Pattern Classification
The Pruned modified fuzzy hyperline segment neural network (PMFHLSNN) is pruned extension of Fuzzy hyperline segment neural network (FHLSNN) with modification in the testing phase. In this paper, a genetic algorithm based rule extractor (GA-PMFHLSNN) is proposed to extract a small set of compact and comprehensible fuzzy if-then rules with high classification accuracy from the PMFHLSNN. After pr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Indonesian Journal of Electrical Engineering and Computer Science
سال: 2018
ISSN: 2502-4760,2502-4752
DOI: 10.11591/ijeecs.v11.i1.pp333-340