Applications of web mining for marketing of online bookstores
Expert Systems with Applications: An International Journal
Non-segmented Document Clustering Using Self-Organizing Map and Frequent Max Substring Technique
ICONIP '09 Proceedings of the 16th International Conference on Neural Information Processing: Part II
Using evidence based content trust model for spam detection
Expert Systems with Applications: An International Journal
A taxonomy of sequential pattern mining algorithms
ACM Computing Surveys (CSUR)
A Lucene and maximum entropy model based hedge detection system
CoNLL '10: Shared Task Proceedings of the Fourteenth Conference on Computational Natural Language Learning --- Shared Task
Opinion digger: an unsupervised opinion miner from unstructured product reviews
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
ICDM'10 Proceedings of the 10th industrial conference on Advances in data mining: applications and theoretical aspects
Exploiting effective features for chinese sentiment classification
Expert Systems with Applications: An International Journal
Combining integrated sampling with SVM ensembles for learning from imbalanced datasets
Information Processing and Management: an International Journal
Evaluating EmotiBlog robustness for sentiment analysis tasks
NLDB'11 Proceedings of the 16th international conference on Natural language processing and information systems
An indent shape based approach for web lists mining
WISM'11 Proceedings of the 2011 international conference on Web information systems and mining - Volume Part II
Feature subsumption for sentiment classification in multiple languages
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
Web usage mining to improve the design of an e-commerce website: OrOliveSur.com
Expert Systems with Applications: An International Journal
Predicting web user behavior using learning-based ant colony optimization
Engineering Applications of Artificial Intelligence
Discovering business intelligence from online product reviews: A rule-induction framework
Expert Systems with Applications: An International Journal
Social networks profile mapping using games
WebApps'12 Proceedings of the 3rd USENIX conference on Web Application Development
Measuring the coverage and redundancy of information search services on e-commerce platforms
Electronic Commerce Research and Applications
On text preprocessing for opinion mining outside of laboratory environments
AMT'12 Proceedings of the 8th international conference on Active Media Technology
Competitive intelligence for SMEs: a web-based decision support system
International Journal of Business Information Systems
Proceedings of the 7th ACM international conference on Web search and data mining
Using linked data to mine RDF from wikipedia's tables
Proceedings of the 7th ACM international conference on Web search and data mining
International Journal of Knowledge-based and Intelligent Engineering Systems - Selected papers of KES2012-Part 2 of 2
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Web mining aims to discover useful information and knowledge from the Web hyperlink structure, page contents, and usage data. Although Web mining uses many conventional data mining techniques, it is not purely an application of traditional data mining due to the semistructured and unstructured nature of the Web data and its heterogeneity. It has also developed many of its own algorithms and techniques. Liu has written a comprehensive text on Web data mining. Key topics of structure mining, content mining, and usage mining are covered both in breadth and in depth. His book brings together all the essential concepts and algorithms from related areas such as data mining, machine learning, and text processing to form an authoritative and coherent text. The book offers a rich blend of theory and practice, addressing seminal research ideas, as well as examining the technology from a practical point of view. It is suitable for students, researchers and practitioners interested in Web mining both as a learning text and a reference book. Lecturers can readily use it for classes on data mining, Web mining, and Web search. Additional teaching materials such as lecture slides, datasets, and implemented algorithms are available online.