Fuzzy Final Homework System Implementation Selected paper: Fuzzy integration of structure adaptive SOMs for web content mining, Fuzzy Sets and Systems 148 (2004) 43–60 Lecture: Prof. Hahn-Ming Lee Student: Ching-Hao Mao

Outline Introduction Proposed method in selected paper Implementation Conclusion References

Introduction In this report, we implement Kim and Cho’s paper appear on Fuzzy Set and System in 2004 User profile represents different aspects of user’s characteristics The author proposed an ensemble of classifiers that estimate user’s preference using web content labeled by user as “like” or “dislike”

Introduction- Preview Studies [2]

Feature Selection Method Properties Feature selection methods such as Information Gain, TFIDF, and ODDS ratio have different properties TFIDF does not consider class values of documents when calculating the relevance of features while information gain uses class labels of documents Odds ratio uses class labels of documents but they find useful features to classify only one specific class

Overview of the proposed method in [1] Classification TFIDF, Information Gain, ODDS Ratio

Structure Adaptive SOM

Training SASOM ’ s using different feature sets Fuzzy Integral Hot Cold or

Data Set Description UCI Syskill & Webert data ( Contain the HTML source of web pages plus the ratings of a single user on these web pages The web pages are on four separate subjects Bands- recording artists (Implement in this report) Goats (Implement in this report) Sheep BioMedical

Implementation Coding Java (J2SE 1.5) program for preprocessing, feature selection (TFIDF and ODDS Ratio), and Fuzzy Integral mechanism Using Weka for Feature Selection (Information Gain) and Classification This report not successfully program SASOM…

Implementation-preprocessing UCI Syskill & Webert data ExtractHTMLContent.java Pure Text without Anchor Text Bands.txt After Stopword and Porter Stemmer Bands_Stopword.txt Bands_Porter.txt

Implementation- Feature Selection In Bands, 61 dataset E.g. Attribute Number: 5436->32 Information GainTFIDFODDS Ratio mother writes places letter movement stories synthesizer songwriters singer america sea acid programming innovative letter method members bleed concentrated mother oss wild cultures vehemently smoking define book charge library hand

Implementation- Fuzzy Integral Fuzzy measure of classifiers that are determined subjectively [1] Bayes Classifier b1,b2,b3 b1=0, b2=1, b3= FuzzyIntegral.java (g1,g2,g3) 0.99,0.99,0.99)(0.01,0.01,0.99) (b1,b2,b3)Result(b1,b2,b3)Result (0,1,0)0.99(0,0,1)0.01 (1,1,1)0.99(0,1,1)0.01 (0,0,0)0,99(0,0,0)0.01

Conclusion Fuzzy integral provides the method of measuring the importance of classifiers subjectively, especially in semi-supervised learning method The method based on fuzzy integral can be effectively applied to web content mining for predicting user’s preference as user profile Fuzzy Integral maybe can apply into my research area to integrate expert or user’s knowledge

References 1. Kyung-Joong Kim, Sung-Bae Cho, Fuzzy integration of structure adaptive SOMs for web content mining, Fuzzy Sets and Systems 148 (2004) 43–60 2. Pazzani M., Billsus, D., Learning and Revising User Profiles: The identification of interesting web sites, Machine Learning 27 (1997),