Relevant bibliographies by topics / Usage profile Web usage mining

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  2. Dissertations / Theses
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Academic literature on the topic 'Usage profile Web usage mining'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Usage profile Web usage mining"

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Zhang, Junwen, Qunqun Xue, and Dalin Zhang. "Mining usage profile to improve web performance testing." International Journal of Services Operations and Informatics 9, no. 3 (2018): 189. http://dx.doi.org/10.1504/ijsoi.2018.094653.

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Zhang, Junwen, Dalin Zhang, and Qunqun Xue. "Mining usage profile to improve web performance testing." International Journal of Services Operations and Informatics 9, no. 3 (2018): 189. http://dx.doi.org/10.1504/ijsoi.2018.10015974.

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Rathipriya, R., K. Thangavel, and J. Bagyamani. "Usage Profile Generation from Web Usage Data Using Hybrid Biclustering Algorithm." International Journal of Applied Evolutionary Computation 2, no. 4 (2011): 37–49. http://dx.doi.org/10.4018/jaec.2011100103.

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Biclustering has the potential to make significant contributions in the fields of information retrieval, web mining, and so forth. In this paper, the authors analyze the complex association between users and pages of a web site by using a biclustering algorithm. This method automatically identifies the groups of users that show similar browsing patterns under a specific subset of the pages. In this paper, mutation operator from Genetic Algorithms is incorporated into the Binary Particle Swarm Optimization (BPSO) for biclustering of web usage data. This hybridization can increase the diversity
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Ms.Dipa, Dixit, and Gadge Jayant. "Automatic Recommendation for Online Users Using Web Usage Mining." International Journal of Managing Information Technology (IJMIT) 2, no. 3 (2010): 33 to 42. https://doi.org/10.5281/zenodo.3357685.

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A real world challenging task of the web master of an organization is to match the needs of user and keep their attention in their web site. So, only option is to capture the intuition of the user and provide them with the recommendation list. Most specifically, an online navigation behavior grows with each passing day,  thus extracting information intelligently from it is a difficult issue. Web master should use web usage mining method to capture intuition. A WUM is designed to operate on web server logs which contain user’s navigation. Hence, recommendation system using WUM can be
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Dipa, Dixit, and Gadge Jayant. "Automatic Recommendation for Online Users Using Web Usage Mining." International Journal of Managing Information Technology (IJMIT) 2, no. 3 (2014): 33 to 42. https://doi.org/10.5281/zenodo.3593612.

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A real world challenging task of the web master of an organization is to match the needs of user and keep their attention in their web site. So, only option is to capture the intuition of the user and provide them with the recommendation list. Most specifically, an online navigation behavior grows with each passing day, thus extracting information intelligently from it is a difficult issue. Web master should use web usage mining method to capture intuition. A WUM is designed to operate on web server logs which contain user’s navigation. Hence, recommendation system using WUM can be used
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John, Joan M., G. Venifa Mini, and E. Arun. "User Profile Tracking by Web Usage Mining in Cloud Computing." Procedia Engineering 38 (2012): 3270–77. http://dx.doi.org/10.1016/j.proeng.2012.06.378.

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Nasraoui, O., M. Soliman, E. Saka, A. Badia, and R. Germain. "A Web Usage Mining Framework for Mining Evolving User Profiles in Dynamic Web Sites." IEEE Transactions on Knowledge and Data Engineering 20, no. 2 (2008): 202–15. http://dx.doi.org/10.1109/tkde.2007.190667.

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An, Kye-Sun, Se-Jin Go, Jun Jiong, and Phill-Kyu Rhee. "Generator of Dynamic User Profiles Based on Web Usage Mining." KIPS Transactions:PartB 9B, no. 4 (2002): 389–90. http://dx.doi.org/10.3745/kipstb.2002.9b.4.389.

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Mallik, Moksud Alam, and Nurul Fariza Zulkurnain. "An Efficient Fuzzy Clustering Algorithm for Mining User Session Clusters on Web Log Data." International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) 2, no. 2 (2022): 80–93. http://dx.doi.org/10.34010/injiiscom.v2i2.7349.

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Data mining is extremely vital to get important information from the web. Additionally, web usage mining (WUM) is essential for companies. WUM permits organizations to create rich information related to the eventual fate of their commercial capacity. The utilization of data that is assembled by Web Usage Mining gives the organizations the capacity to deliver results more compelling to their organizations and expanding of sales. Client access patterns can be mined from web access log information using Web Usage Mining (WUM) techniques. Because there are so many end-user sessions and URL resourc
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Jenifer, Mahilraj. "Trajectory Based Location Prediction and Enriched Ontological User Profiles for Efficient Website Recommendation." International Journal of Recent Technology and Engineering (IJRTE) 9, no. 3 (2020): 250–57. https://doi.org/10.35940/ijrte.C4363.099320.

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The spread over of huge amount of information in the vast area of internet makes difficult for the users to obtain the search items that are relevant to them. The adoption of web usage mining helps to discover the accurate search results that satisfy their requirements. To fulfill their need, it is necessary to know their preferences of search at various contexts. In general, the user profiles are used to determine the taste of the users. The traditional method of user profiling does not provide a complete detail regarding their search. In addition, the search preference of the individuals var
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Dissertations / Theses on the topic "Usage profile Web usage mining"

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Vollino, Bruno Winiemko. "Descoberta de perfis de uso de web services." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2013. http://hdl.handle.net/10183/83669.

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Durante o ciclo de vida de um web service, diversas mudanças são feitas na sua interface, eventualmente causando incompatibilidades em relação aos seus clientes e ocasionando a quebra de suas aplicações. Os provedores precisam tomar decisões sobre mudanças em seus serviços frequentemente, muitas vezes sem um bom entendimento a respeito do efeito destas mudanças sobre seus clientes. Os trabalhos e ferramentas existentes não fornecem ao provedor um conhecimento adequado a respeito do uso real das funcionalidades da interface de um serviço, considerando os diferentes tipos de consumidores, o que
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Benkovská, Petra. "Web Usage Mining." Master's thesis, Vysoká škola ekonomická v Praze, 2007. http://www.nusl.cz/ntk/nusl-3950.

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General characteristic of web mining including methodology and procedures incorporated into this term. Relation to other areas (data mining, artificial intelligence, statistics, databases, internet technologies, management etc.) Web usage mining - data sources, data pre-processing, characterization of analytical methods and tools, interpretation of outputs (results), and possible areas of usage including examples. Suggestion of solution method, realization and a concrete example's outputs interpretation while using above mentioned methods of web usage mining.
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Oosthuizen, Craig Peter. "Web usage mining of organisational web sites." Thesis, Nelson Mandela Metropolitan University, 2005. http://hdl.handle.net/10948/399.

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Web Usage Mining (WUM) can be used to determine whether the information architecture of a web site is structured correctly. Existing WUM tools however, do not indicate which web usage mining algorithms are used or provide effective graphical visualisations of the results obtained. WUM techniques can be used to determine typical navigation patterns of the users of organisational web sites. An organisational web site can be described as a site which has a high level of content. The Computer Science & Information Systems (CS&IS) web site at the Nelson Mandela Metropolitan University (NMMU) is an
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Norguet, Jean-Pierre. "Semantic analysis in web usage mining." Doctoral thesis, Universite Libre de Bruxelles, 2006. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210890.

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With the emergence of the Internet and of the World Wide Web, the Web site has become a key communication channel in organizations. To satisfy the objectives of the Web site and of its target audience, adapting the Web site content to the users' expectations has become a major concern. In this context, Web usage mining, a relatively new research area, and Web analytics, a part of Web usage mining that has most emerged in the corporate world, offer many Web communication analysis techniques. These techniques include prediction of the user's behaviour within the site, comparison between expected
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Abou, Latif Firas. "Identification du profil des utilisateurs d’un hypermédia encyclopédique à l’aide de classifieurs basés sur des dissimilarités : création d’un composant d’un système expert pour Hypergéo." Thesis, Rouen, INSA, 2011. http://www.theses.fr/2011ISAM0004/document.

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L’objectif de cette thèse est d’identifier le profil d’utilisateur d’un hypermédia afin de l’adapter. Ceprofil est déterminé en utilisant des algorithmes d’apprentissage supervisé comme le SVM.Le modèle d’utilisateur est l’un des composants essentiels des hypermédias adaptatifs. Une des façons de caractériser ce modèle est d’associer l’utilisateur à un profil. Le Web Usage Mining (WUM)identifie ce profil à l’aide des traces de navigation. Toutefois, ces techniques ne fonctionnent généralement que sur de gros volumes de données. Dans le cadre de volumes de données réduits, nous proposons d’util
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Ba-Omer, Hafidh Taher. "A framework for educational web usage mining." Thesis, University of Manchester, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.492063.

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Salin, Suleyman. "Web Usage Mining And Recommendation With Semantic Information." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/12610483/index.pdf.

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Web usage mining has become popular in various business areas related with Web site development. In Web usage mining, the commonly visited navigational paths are extracted in terms of Web page addresses from the Web server visit logs, and the patterns are used in various applications. The semantic information of the Web page contents is generally not included in Web usage mining. In this thesis, a framework for integrating semantic information with Web usage mining is implemented. The frequent navigational patterns are extracted in the forms of ontology instances instead of Web page addresses
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Khairo-Sindi, Mazin Omar. "Framework for web log pre-processing within web usage mining." Thesis, University of Manchester, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.488456.

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Web mining is gaining popularity by the day and the role of the web in providing invaluable information about users' behaviour and navigational patterns is now highly appreciated by information technology specialists and businesses alike. Nevertheless, given the enormity of the web and the complexities involved in delivering and retrieving electronic information, one can imagine the difficulties involved in extracting a set of minable objects from the raw and huge web log data. Added to the fact that web mining is a new science, this may explain why research on data pre-processing is still lim
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Lou, Wenwu. "Characterizing Web linking and usage with hierarchical models /." View abstract or full-text, 2005. http://library.ust.hk/cgi/db/thesis.pl?COMP%202005%20LOU.

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Karlsson, Sophie. "Datainsamling med Web Usage Mining : Lagringsstrategier för loggning av serverdata." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-9467.

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Webbapplikationers komplexitet och mängden avancerade tjänster ökar. Loggning av aktiviteter kan öka förståelsen över användares beteenden och behov, men används i för stor mängd utan relevant information. Mer avancerade system medför ökade krav för prestandan och loggning blir än mer krävande för systemen. Det finns behov av smartare system, utveckling inom tekniker för prestandaförbättringar och tekniker för datainsamling. Arbetet kommer undersöka hur svarstider påverkas vid loggning av serverdata, enligt datainsamlingsfasen i web usage mining, beroende på lagringsstrategier. Hypotesen är at
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Books on the topic "Usage profile Web usage mining"

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Zaïane, Osmar R., Jaideep Srivastava, Myra Spiliopoulou, and Brij Masand, eds. WEBKDD 2002 - Mining Web Data for Discovering Usage Patterns and Profiles. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/b11784.

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Osmar, Zaïane, ed. WEBKDD 2002: Mining Web data for discovering usage patterns and profiles : 4th international workshop, Edmonton, Canada, July 23, 2002 : revised papers. Springer, 2003.

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Zhang, Haizheng, Myra Spiliopoulou, Bamshad Mobasher, et al., eds. Advances in Web Mining and Web Usage Analysis. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00528-2.

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Nasraoui, Olfa, Osmar Zaïane, Myra Spiliopoulou, Bamshad Mobasher, Brij Masand, and Philip S. Yu, eds. Advances in Web Mining and Web Usage Analysis. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11891321.

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Mobasher, Bamshad, Olfa Nasraoui, Bing Liu, and Brij Masand, eds. Advances in Web Mining and Web Usage Analysis. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11899402.

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Nasraoui, Olfa, Myra Spiliopoulou, Jaideep Srivastava, Bamshad Mobasher, and Brij Masand, eds. Advances in Web Mining and Web Usage Analysis. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-77485-3.

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Taniar, David, and Lukman Hakim Iwan. Exploring advances in interdisciplinary data mining and analytics: New trends. Information Science Reference, 2012.

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Kamvar, Sep. We feel fine: An almanac of human emotion. Scribner, 2009.

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Kamvar, Sep. We feel fine: An almanac of human emotion. Scribner, 2009.

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Kenkyūjo, Mitsubishi Sōgō, ed. Heisei 19-nendo Keizai Sangyōshō jōhō daikōkai purojekuto (kiban kyōtsū gijutsu kaihatsu to kenshō). Mitsubishi Sōgō Kenkyūjo, 2008.

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Book chapters on the topic "Usage profile Web usage mining"

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Zhang, Yanchun, Guandong Xu, and Xiaofang Zhou. "A Latent Usage Approach for Clustering Web Transaction and Building User Profile." In Advanced Data Mining and Applications. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11527503_6.

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Xu, Guandong, Yanchun Zhang, and Lin Li. "Web Usage Mining." In Web Mining and Social Networking. Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-7735-9_6.

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Liu, Bing, Bamshad Mobasher, and Olfa Nasraoui. "Web Usage Mining." In Web Data Mining. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19460-3_12.

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Román, Pablo E., Gastón L’Huillier, and Juan D. Velásquez. "Web Usage Mining." In Advanced Techniques in Web Intelligence - I. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14461-5_6.

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Castellano, Giovanna, Anna M. Fanelli, and Maria A. Torsello. "Web Usage Mining: Discovering Usage Patterns for Web Applications." In Advanced Techniques in Web Intelligence-2. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-33326-2_4.

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Suryavanshi, Bhushan Shankar, Nematollaah Shiri, and Sudhir P. Mudur. "Adaptive Web Usage Profiling." In Advances in Web Mining and Web Usage Analysis. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11891321_7.

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Kim, Haeng-Kon, and Roger Y. Lee. "Frameworks for Web Usage Mining." In Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01203-7_10.

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Rossi, Fabrice, Francisco De Carvalho, Yves Lechevallier, and Alzennyr Da Silva. "Dissimilarities for Web Usage Mining." In Studies in Classification, Data Analysis, and Knowledge Organization. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/3-540-34416-0_5.

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Abraham, Ajith. "World Wide Web Usage Mining." In Computationally Intelligent Hybrid Systems. John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9780471683407.ch11.

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da Silva, Alzennyr, Yves Lechevallier, Fabrice Rossi, and Francisco de Carvalho. "Clustering Dynamic Web Usage Data." In Innovative Applications in Data Mining. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-88045-5_4.

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Conference papers on the topic "Usage profile Web usage mining"

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Xu, Jing, Fei Xu, Fanshu Ma, Lei Zhou, Shuanglin Jiang, and Zhibo Rao. "Mining Web Usage Profiles from Proxy Logs: User Identification." In 2021 IEEE Conference on Dependable and Secure Computing (DSC). IEEE, 2021. http://dx.doi.org/10.1109/dsc49826.2021.9346276.

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G., Kalyani, and Eswara Reddy B. "A Framework for Mining Evolving user Profiles on Web Usage." In International Conference on Computer Applications — Database Systems. Research Publishing Services, 2010. http://dx.doi.org/10.3850/978-981-08-7300-4_0082.

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El Aissaoui, Ouafae, Yasser El Madani El Alami, Lahcen Oughdir, and Youssouf El Allioui. "Integrating web usage mining for an automatic learner profile detection: A learning styles-based approach." In 2018 International Conference on Intelligent Systems and Computer Vision (ISCV). IEEE, 2018. http://dx.doi.org/10.1109/isacv.2018.8354021.

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Rajput, Anil, and Nidhi Chandel. "Web usage mining." In the International Conference & Workshop. ACM Press, 2011. http://dx.doi.org/10.1145/1980022.1980384.

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Madiraju, Praveen, and Yanqing Zhang. "Web usage data mining agent." In AeroSense 2002, edited by Belur V. Dasarathy. SPIE, 2002. http://dx.doi.org/10.1117/12.460231.

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Omar, Rosli, and Zainatul Shima Abdullah. "Mining Web Usage Using FRS." In 2018 International Conference on Information and Communication Technology for the Muslim World (ICT4M). IEEE, 2018. http://dx.doi.org/10.1109/ict4m.2018.00062.

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Hollink, Laura, Peter Mika, and Roi Blanco. "Web usage mining with semantic analysis." In the 22nd international conference. ACM Press, 2013. http://dx.doi.org/10.1145/2488388.2488438.

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Aggarwal, Saloni, and Veenu Mangat. "Application Areas of Web Usage Mining." In 2015 Fifth International Conference on Advanced Computing & Communication Technologies (ACCT). IEEE, 2015. http://dx.doi.org/10.1109/acct.2015.115.

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Chen, Junjie, and Wei Liu. "Research for Web Usage Mining Model." In 2006 International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (CIMCA'06). IEEE, 2006. http://dx.doi.org/10.1109/cimca.2006.179.

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Nina, Shahnaz Parvin, Mahmudur Rahman, Khairul Islam Bhuiyan, and Khandakar Entenam Unayes Ahmed. "Pattern Discovery of Web Usage Mining." In 2009 International Conference on Computer Technology and Development. IEEE, 2009. http://dx.doi.org/10.1109/icctd.2009.199.

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