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Web usage mining

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TheWebisaliveenvironmentthatmanagesanddrivesawidespectrumofapp- cations in which a user may interact with a company, a governmental authority, a non-governmental organization or other non-pro?t institution or other users. User preferences and expectations, together with usage patterns, form the basis for personalized, user-friendly and business-optimal services. Key Web business metrics enabled by proper data capture and processing are essential to run an e?ective business or service. Enabling technologies include data mining, sc- able warehousing and preprocessing, sequence discovery, real time processing, document classi?cation, user modeling and quality evaluation models for them. Recipient technologies required for user pro?ling and usage patterns include recommendation systems, Web analytics applications, and application servers, coupled with content management systems and fraud detectors. Furthermore, the inherent and increasing heterogeneity of the Web has - quired Web-based applications to more e?ectively integrate a variety of types of data across multiple channels and from di?erent sources. The development and application of Web mining techniques in the context of Web content, Web usage, and Web structure data has already resulted in dramatic improvements in a variety of Web applications, from search engines, Web agents, and content management systems, to Web analytics and personalization services. A focus on techniques and architectures for more e?ective integration and mining of c- tent, usage,and structure data from di?erent sourcesis likely to leadto the next generation of more useful and more intelligent applications.

Web usage mining --- Internet users --- Analyse du comportement des internautes (Informatique) --- Internautes --- Congresses. --- Congrès --- Computer Science --- Mechanical Engineering - General --- Library & Information Science --- Engineering & Applied Sciences --- Mechanical Engineering --- Social Sciences --- Information Technology --- Artificial Intelligence --- Analysis, Web usage --- Analytics, Web --- Mining, Web usage --- Web analytics --- Web usage analysis --- Web users --- World Wide Web users --- Computer science. --- Computer communication systems. --- Database management. --- Information storage and retrieval. --- Artificial intelligence. --- Computers and civilization. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Computer Communication Networks. --- Database Management. --- Information Storage and Retrieval. --- Information Systems Applications (incl. Internet). --- Computers and Society. --- Civilization and computers --- Civilization --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Network computers --- Informatics --- Science --- Distributed processing --- Data mining --- Computer users --- Personal Internet use in the workplace --- Information storage and retrieva. --- Artificial Intelligence. --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval --- Application software. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software

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Sociology & Social History --- Social Sciences --- Social Change --- Information Technology --- Computer Science (Hardware & Networks)

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Artificial intelligence. --- Computer communication systems. --- Information storage and retrieval. --- User interfaces (Computer systems). --- Computers and civilization. --- Information technology. --- Business—Data processing. --- Artificial Intelligence. --- Computer Communication Networks. --- Information Storage and Retrieval. --- User Interfaces and Human Computer Interaction. --- Computers and Society. --- IT in Business. --- Web sites --- Web site development --- Design --- Authoring programs

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Web personalizationcan be de?ned as any set of actions that can tailor the Web experience to a particular user or set of users. The experience can be something as casualas browsinga Web site oras (economically)signi?cantas tradingstock or purchasing a car. The actions can range from simply making the presentation more pleasing to anticipating the needs of a user and providing customized and relevant information. To achieve e?ective personalization, organizations must rely on all available data, including the usage and click-stream data (re?e- ing user behavior), the site content, the site structure, domain knowledge, user demographics and pro?les. In addition, e?cient and intelligent techniques are needed to mine these data for actionable knowledge, and to e?ectively use the discovered knowledge to enhance the users' Web experience. These techniques must address important challenges emanating from the size and the heteroge- ity of the data, and the dynamic nature of user interactions with the Web. E-commerce and Web information systems are rich sources of di?cult pr- lems and challenges for AI researchers. These challenges include the scalability of the personalization solutions, data integration, and successful integration of techniques from machine learning, information retrievaland ?ltering, databases, agent architectures, knowledge representation, data mining, text mining, stat- tics, user modelling and human-computer interaction. Throughout the history of the Web, AI has continued to play an essential role in the development of Web-based information systems, and now it is believed that personalization will prove to be the killer-app  for AI.

Computer architecture. Operating systems --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- IR (information retrieval) --- bedrijfseconomie --- informatica --- maatschappij --- informatica management --- computernetwerken --- robots