Paper Info
Title
An Opinion Mining Approach For Web User Identification And Clients' Behaviour Analysis
Abstract
this paper describes functions of a system designed for the behavior analysis of e-commerce clients. It enables user identification and client behavior extraction for interacting with web site customers. General approaches used in the field of Web Usage Mining are presented together with proposals to extend the data base with the information gained from e-commerce site forums and queries. Our system carries out an evaluation and rating of opinions, and our approach is based on linguistic and the statistic treatment of natural language. Three different methods for classifying opinions from clients' forum are used, and two new methods, based on linguistic knowledge to assign a mark dependent upon the client's emotions and opinions described in forum comments, have been introduced.
Year
Venue
Keywords
2013
2013 FIFTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL ASPECTS OF SOCIAL NETWORKS (CASON)
Web Usage Mining, Opinion Mining, NLP, User Behaviour Analysis, User Identification, Personalization
Field
DocType
ISSN
Data mining,World Wide Web,Web mining,Statistic,Consumer behaviour,Computer science,Sentiment analysis,Natural language,Web site
Conference
2155-7047
Citations 
PageRank 
References 
2
0.40
11
Authors
3
Name
Order
Citations
PageRank
Grzegorz Dziczkowski1122.88
Katarzyna Wegrzyn-wolska25811.65
Lamine Bougueroua383.25