utilisation du web mining en e-commerce

Utilisation du Web Miningen E-Commerce

Par Jianfeng NIE

Mars 29, 2006

29 Mars, 2006 Utilisation du Web Mining en E-commerce 2

Plan

IntroductionTaxonomie du Web MiningProcessus d’extraire des connaissances dans Web MiningApplication du Web Mining en E-commerceConclusion


Plan

IntroductionDéfinition du Web MiningProblématiqueHistoire

Taxonomie du Web MiningProcessus d’extracter des connaissances dans Web MiningApplication du Web Mining en E-commerceConclusion


Introduction (1/3)

Web Mining:s’est développé à la fin des années 90. ce domaine consiste à utiliser l’ensemble des techniques du Data Mining afin de développer des approches et des outils, permettant d’extraire des informations pertinentes à partir de données du web (documents, traces d’interactions, structure des pages, des liens……)


Introduction (2/3)

Problématique : Pourquoi Web MiningTrouver l’information du web n’est plus facile.

Information est trop.Structure du web est complexe.Changement est fréquent

Data Mining vise souvent à traiter des données déjà organisées dans une base de données.

E-Commerce is the killer of the informaion.Stratégie, business intélligentSérvices personalisé


Introduction (3/3)

Histoire:Terme créé par Etzioni en 1996Taxonomie du Web Mining (Chang et al., 2001;

Chakrabarti, 2003)


Plan

IntroductionTaxonomie du Web Mining

Web Content MiningWeb structure MiningWeb Usage Mining

Processus d’extraire des connaissances dans Web MiningApplication du Web Mining en E-commerceConclusion


Taxonomie du Web Mining

Web MiningWeb Mining

Web Content Mining

Web Content Mining

WebStructure

Mining

WebStructure

Mining

Web Usage Mining

Web Usage Mining


Web Content Mining (3-1)

Recherche d’information (RI) (1/2)

Précision = documents pertinents retrouvés / documents retrouvés

Rappel = documents pertinents retrouvés / documents pertinents


Web Content Mining

Web Content Mining Web

Structure Mining

WebStructure

MiningWeb Usage

Mining

Web Usage Mining


Web Content Mining (3-1)

Classification du Contenu (2/2)

Exemple: Pour trouver le site web de l’U de MDirectory Regional Countries Canada > Provinces and > > > Territories > Québec > Regions > Montréal > Cities > Montréal Education> > College and University

Education Science Business News

Yahoo home page

UniversityCollege Companies Finance Jobs……


Web Content Mining


Structure Mining

WebStructure

MiningWeb Usage

Mining

Web Usage Mining

http://us.rd.yahoo.com/dir/catpg/path/*http:/dir.yahoo.com/

http://us.rd.yahoo.com/dir/catpg/path/*http:/dir.yahoo.com/Regional/

http://us.rd.yahoo.com/dir/catpg/path/*http:/dir.yahoo.com/Regional/Countries/

http://us.rd.yahoo.com/dir/catpg/path/*http:/dir.yahoo.com/Regional/Countries/Canada/

http://us.rd.yahoo.com/dir/catpg/path/*http:/dir.yahoo.com/Regional/Countries/Canada/Provinces_and_Territories/







http://us.rd.yahoo.com/dir/catpg/path/*http:/dir.yahoo.com/Regional/Countries/Canada/Provinces_and_Territories/Quebec/Regions/Montreal/Cities/Montreal/Education/


Web Structure Mining (3-2)

Visualization du web (1/4)

Source: Grobelnik, Marko (2001) Web-Mining…searching for the knowledge on the Internet…


Web Content Mining


Structure Mining

WebStructure

MiningWeb Usage

Mining

Web Usage Mining



Structure du Web (2/4)

Source:Linoff, Gordon S. et Berry, Michael J.A. (2001) Mining the Web: Transforming customer Data into Customer Value


Web Content Mining


Structure Mining

WebStructure

MiningWeb Usage

Mining

Web Usage Mining



Hubs et Autorités (3/4)


Web Content Mining


Structure Mining

WebStructure

MiningWeb Usage

Mining

Web Usage Mining

Hubs Authorités



Algorithme de HITS (4/4)Sommation

(v, u) est un lien de citation : la page v cite la page u

Normalisation

et


Web Content Mining


Structure Mining

WebStructure

MiningWeb Usage

Mining

Web Usage Mining

∑∈

=Euvu

vhua),(:

)()( ∑∈

=Euvu

vaua),(:

)()(

[ ]∑=

q

qa

uaua2)(

)()([ ]∑

=q

qh

vhua 2)(

)()(


Problème: Web Mining =RI ?

Non:Il y a des différences importantes:

Résultat et ButTâcheFonctionEtc.


Web Usage Mining (3-3)

Web Usage MiningAnalyse du comportement de l’utilisateur àtravers sa navigation et notamment l’ensemble des clics effectués sur le site (clickstream).


Web Content Mining


Structure Mining

WebStructure

MiningWeb Usage

Mining

Web Usage Mining


Web Usage Mining (3-3)

Serveur Log

Source: Sanjay Kumar Madria (2002) Web Mining: A Bird’s Eye View, University of Missouri-Rolla


Web Content Mining


Structure Mining

WebStructure

MiningWeb Usage

Mining

Web Usage Mining


Plan

IntroductionTaxonomie du Web MiningProcessus d’extraire des connaissances dans Web Mining

Préparation de donnéesOLAPAnalyse (Data Mining)

Application du Web Mining en E-commerceConclusion


Processus d’extraire des connaissances dans Web Mining

Source: Zaiane Osmar R. and Cai JiAn (2001), ‘Web Mining: From Concepts to Practical Systems’, DASFAA’2001


Processus d’extraire des connaissances dans Web Mining(3-1)

Préparation de données (1/2)

Capturer les données

Nettoyer les données

Transformer les données



Préparation de données (2/2)Un exemple de la data transformé

Source:Zaiane Osmar R., Xin Man and Han Jiawei (1998)



OLAP (1/3)

Source: Zhang Zhongping (2001) Introduction of OLAP


Processus d’extraire des connaissances dans Web Mining(3-2)Cube de données (2/3)

Source:Zaiane Osmar R. and Cai JiAn (2001), ‘Web Mining: From Concepts to Practical Systems’, DASFAA’2001

sum

0-20K20-40K 60K- sumAgrigolture

… ...

sum

Accounting

Province

Industrie

40-60KB.C.Prairies

Ontario

Salaire


Processus d’extraire des connaissances dans Web Mining(3-2)Cube de données (3/3)

sum

0-20K20-40K 60K- sumAgrigolture

… ...

sum

Accounting

Province

Industrie

40-60KB.C.Prairies

Ontario

Salaire



Analyse (Data Mining)Analyse de route

Association

Classification et prédiction

Clustering



Analyse (Data Mining)(1/4)Analyse de route

80% clients visite le site par ‘compagnie/produit2 ’, mais pas par la page d’accueil. 55% clients visite moins de 5 pages web avant sortir.……



Analyse (Data Mining) (2/4)Association

pour mesurer l’association entre deux items. ‘right’ est le poids de transformer du nceud ‘i’ au nceud ‘t’. Si la valeur de ‘right’ > 0.5, on pense que les deux noeuds ont un lien fort. Ce lien signifie qu’un client qui visite la page A va souvent visiter la page B aussi.

[ ])(,),( ti iNrightiN { }niiiI ,...,, 21=



Analyse (Data Mining) (3/4)Classification Bayesianne

Idea: assign to example X the class label C such that P(C|X) is maximalComputes the distribution of an input associated with each class, for example, given the variable X with a value at xi the probability of it being in Class A is greater than it being in Class B

Source: Auvil, Loreta et Searsmith Duane (2003)

Mathematically speaking — If one knows how P(X | C), and the densities P(xi) and P(cj) (prior probabilities) are known then the classifier is one which assigns class cj to datum xi if cj has the highest posterior probability given the data.



Analyse (Data Mining) (4/4)Clustering

L=(ip, uid, url, time) Ip, uid, url, time sont l’adresse du client, l’identification du client, l’ URL qui est demandé par le client, le temps de navigation du visiteur

URL

CCC

CCCCCC

M

UID

mnmm

n

n

nm

4444 84444 76

⎪⎪⎭

⎪⎪⎬

⎫

⎥⎥⎥⎥

⎦

⎤

⎢⎢⎢⎢

⎣

⎡

=×

...............

...

...

21

22221

11211


Plan

IntroductionTaxonomie du Web MiningProcessus d’extraire des connaissances dans Web MiningApplication du Web Mining en E-commerce

Système de recommandationConclusion


Application du Web Mining

Source: J. Srivastava, R. Cooley, M. Deshpande et PN Tan (2000) Web Usage Mining: Discovery and Applications of Usage Patterns from Web Data, SIGKDD Explorations

Site M odification

Business Intelligence

System Improvement

Personalization

Web Usage Mining

Usage Characterization

WebSIFT WUM SpeedTracer WebLogMiner Shahabi

Site Helper Letizia Web Watcher Mobasher Analog Krishnapuram

Rexford Schecter Aggarwal

Adaptive Sites SurfAid Buchner Tuzhilin

Pitkow Arlitt Manley Almeida


Application du Web Mining en E-commerce

Système de Recommandation

le magasin peut recommander le produit qui peut être intéressant au client selon plusieurs critères :

la correspondance du produit au profil du client ;la similarité du produit aux produits que le client a déjàachetés auparavant ;l’appréciation des autres clients similaires au client.


Application du Web Mining en E-commerce

Système de Recommandation Architecture

Source: Markellou, Mousourouli, Sirmakessis et Tsakalidis (2005)


Plan

IntroductionTaxonomie du Web MiningProcessus d’extraire des connaissances dans Web MiningApplication du Web Mining en E-commerceConclusion


Conclusion

Il y a lien forte entre Web Mining et E-commerceWeb Mining utilise des outils mûres, par exemple, des méthodes de RI, Data Miningetc. Il y a des limitations du Web Mining

Dépendre très forte sur le ficher de logLe bruite d’informationOLAP est complexe et cher


Références

Auvil, Loretta et Searsmith Duane (2003) Using Text Mining for Spam Filtering, University of IllinoisGrobelnik, Marko (2001) Web-Mining…searching for the knowledge on the Internet… , InstitutJožef Stefan http://www-ai.ijs.si/MarkoGrobelnik/J. Srivastava, R. Cooley, M. Deshpande et PN Tan (2000) Web Usage Mining: Discovery and Applications of Usage Patterns from Web Data, SIGKDD ExplorationsSanjay Kumar Madria (2002) Web Mining: A Bird’s Eye View, University of Missouri-RollaVipin Kumar (2002) Army High Performance Computing Research Center,University of MinnesotaZhang Zhongping (2001), Introduction of OLAP http://www.dmgroup.org.cn/pptdown050322/OLAPIntr.ppt

http://www-ai.ijs.si/MarkoGrobelnik/

http://www.dmgroup.org.cn/pptdown050322/OLAPIntr.ppt


Référence

[1]Amazon.com (2004), Annual Report[2]Abraham Ajith (2003), ‘Business Intelligence from Web Usage Mining’, Journal of Information & Knowledge Management, Vol. 2, No. 4, PP375-390[3]Ansari Suhail, Kohavi Ron, Mason Llew and Zheng Zijian (2000), ‘Integrating E-commerce and Data Mining: Architecture and Challenges’, WEBKDD ‘2000 Workshop[4]Baraglia Ranieri and Palmerini Paolo (2002), ‘Suggest: A Web Usage Mining System’, IEEE International Conference on Information Technology (ITCC’02)[5]Barnes & Noble.com (2004), Annual Report[6]Buchner Alex G. and Mulvenna Maurice D. (1998), ‘Discovering Internet Marketing Intelligence through Online Analytical Web Usage Mining’, SIGMOD Record, Vol. 27, No. 4[7]Castellano Marcello, Pastore Nicola and Arcieri Francesco (2005), ‘A Flexible Mining Architecture for Providing New E-knowledge Services’, IEEE 38th Hawaii International Conference on System Sciences[8]Chakrabarti Soumen (2000), ‘Data Mining for Hypertext: A Tutorial Survey’, ACM SIGKDD, Volume 1, Issue 2[9]Chie Ed H., Rosien Adam and Heer Jeffrey (2000), ‘Lumber Jack: Intelligent Discovery and Analysis of Web User Traffic Composition’, Working Paper[10]Cooley Robert, Mobasher Bamshad and Srivastava Jaideep (1999), ‘Data Preparation for Mining World Wide Web Browsing Patterns’, Working Paper, University of Minnesota[11]Ebay.com (2004), Annual Report[12]Eirinaki, M. and Vazirgiannis, M. (2003), ‘Web Mining for Web Personalization’, ACM Transactions on Internet Technology, 2003, 3(1), PP1-27[13]Gomory Stephen, Hoch Robert, Lee Juhnyoung, Podlaseck Mark and Schonberg Edith(1999), ‘E-commerce Intelligence: Measuring, Analyzing, and Reporting on Merchandising Effectiveness of Online Stores’, Working Paper, IBM T. J. Watson Research Center[14]Grcar Miha(2004), ‘User Profiling: Web Usage Mining’, SIKDD’2004 at Multiconference, IS 2004, PP12-15[15]Hu Xiaohua and Cercone Nick (2002), ‘An OLAM Framework for Web Usage Mining and Business Intelligence Reporting’, IEEE Volume 2, PP 950 -955[16]Jespersen Soren E., Thorhauge Jesper and Pedersen Torben Bach (2002), ‘A Hybrid Approach to Web Usage Mining’, Technical Report 02-5002, Aalborg University[17]Ji Junzhong, Sha Zhiqiang, Liu Chunnian and Zhong Ning (2003), ‘Online Recommendation Based on Customer Shopping Model in E-commerce’, IEEE/WIC, WI’03[18]Joo Dongkwon and Moon Songchun (2001), ‘Scalable Web Mining Architecture for Backward Induction in Data Warehouse Environment’, IEEE Catalogue No. 01CH37239[19]Kawano Hiroyuki (2004), ‘Applications of Web Mining: From Web Search Engine to P2P Filtering’, IEEE 12th International conference on Informatics Research for Development of Knowledge Society Infrastructure (ICKS’04)[20]Kohavi Ron (2001), ‘Mining E-commerce Data: The Good, the Bad, and the Ugly’, 7th ACM SIGKDD Intl' Conf. on Knowledge Discovery and Data Mining (KDD '01) [21]Kohavi Ron, Provost Foster (2001), ‘Applications of Data Mining to Electronic Commerce’, Data Mining and Knowledge Discovery, 5, 5-10, KluwerAcademic Publishers


Référence

[22]Kohavi Ron, Mason Llew, Parekh Rajesh and Zheng Zijian (2004), ‘Lessons and Challenges from Mining Retail E-commerce Data’, Machine Learning Journal, Special Issue on Data Mining lessons learned[23]Kosala Raymond and Blockeel Hendrik (2000), ‘Web Mining Research: A Survey’, SIGKDD Explorations, Volume 2, Issue 1[24]Kwan Irene S. Y. (2005), ‘Towards Effective Web Resources Management: An Empirical Study and a Web Mining Approach’, IEEE the Fifth International Conference on System Sciences[25]Lee Chung-Hong and Yang Hsin-Chang (2001), ‘Developing an Adaptive Search Engine for E-commerce Using a Web Mining Approach’, IEEE[26]Linoff Gordon S. and Berry Michael J.A. (2001), ‘Mining the Web: Transforming Customer Data into Customer Value’, John Wiley & Sons[27]Liu Lizhen, Chen Junjie and Song Hantao (2001), ‘The Research of Web Mining’, IEEE 4th World Congress on Intelligent Control and Automation[28]Liu Jian-guo, Huang Zheng-hong and Wu Wei-ping (2003), ‘Web Mining for Electronic Business Application’, IEEE[29]Li Jia and Zaiane Osmar. R (2004), ‘Using Distinctive Information Channels for a Mission-based Web Recommender System’, 6th ACM SIGKDD workshop on Webmining and Web Analysis (WebKDD 2004), PP 35-46[30]Markellou Penelope, Mousourouli Ioanna, Sirmakessis Spiros and Tsakalidis Athanasios (2005), ‘Personalized E-commerce Recommendations’, IEEE International Conference on E-business Engineering (ICEBE’05)[31]Mena Jesus (1999), ‘Mining E-custor Behavior’, DB2 Magazine, Vol. 4, Issue 4, http://www.db2mag.com/db_area/archives/1999/q4/mena.shtml[32]Mobasher Bamshad, Jain Namit, Han Eui-Hong and Srivastava Jaideep (1997), ‘Web Mining: Pattern Discovery from World Wide Web Transactions’, Working paper, University of Minnesota[33]Pal Sankar K, Talwar Varun and Mitra Pabitra (2002), ‘Web Mining in Soft Computing Framework: Relevance, State of the Art and Future Directions’, IEEE Transactions on Neural Networds, Vol. 13, No. 5[34]Perner Petra (2002), ‘Advances in Data Mining: Applications in E-commerce, Medicine, and Knowledge Management’, Springer, LNAI2394[35]Punin John R., Krishnamoorthy Mukkai S. and Zaki Mohammed J. (2001), ‘Web Usage Mining – Languages and Algorithms’, In Studies in Classification, Data Analysis and Knowledge Organization, Springer-Verlag, 2001. RPI Tech Report 01-3[36]Roy Nivedita and Mphapaatra Tapas (2005), ‘Web Mining: A Key Enabler in E-business’, IEEE ICSSSM '05 International Conference[37]Sarwar Badrul, Darypis George, Konstan Joseph and Riedl John (2000), ‘Analysis of Recommendation Algorithms for E-commerce’, Technical Report, ACM, University of Minnesota[38]Scime Anthony (2005), ‘Web Mining : Applications and Techniques’, Idea Group Publishing[39]Stefani A., Vassiliadis B. and Xenos M. (2004), ‘Behavioral Patterns in Hypermedia Systems: A Short Study of E-commerce vs. E-learning Practices’, EPEAEKII Iraklitos programme at HOU[40]Wang Jicheng, Huang Yuan, Wu Gangshan and Zhang Fuyan (1999), ‘Web Mining: Knowledge Discovery on the Web’, IEEE, Volume. 2, PP 137 -141 vol.2[41]Web-datamining.net, ‘FAQ, web mining’http://www.web-datamining.net/forum/faq_wm.asp[42]Yun Chin-Huang and Chen Ming-Syan (2000), ‘Mining Web Transaction Patterns in an Electronic Commerce Environment’, Pacific-Asia Conference on Knowledge Discovery and Data Mining

http://www.db2mag.com/db_area/archives/1999/q4/mena.shtml


Référence

[43]Zaiane Osmar R., Xin Man and Han Jiawei (1998), ‘Discovering Web Access Patterns and Trends by Applying OLAP and Data Mining Technology on Web logs’, Advances in Digital Libraries Conference, PP 19--29[44]Zaiane Osmar R. (2001), ‘Web Usage Mining for a Better Web-Based Learning Environment’, Conference on Advanced Technology for Education, pages 60--64[45]Zaiane Osmar R. and Cai JiAn (2001), ‘Web Mining: From Concepts to Practical Systems’, DASFAA’2001


Merci à Votre Attention


Bienvenu votreConseil et Question

utilisation du web mining en e-commerce

Documents