Data Mining by Mehmed Kantardzic (good book recommendations TXT) 📕

Way from Data Mining to Web Log Mining, Computer Systems in Science & Engineering, Vol. 2, 1999, pp. 113–125.

Thuraisingham, B., Managing and Mining Multimedia Databases, CRC Press LLC, Boca Raton, FL, 2001.

Witten, I. H., E. Frank, Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations, Morgan Kaufmannn Publ., Inc., New York, 1999.

Wu, X., et al., Top 10 Algorithms in Data Mining, Knowledge and Information Systems, Vol. 14, 2008, pp. 1–37.

Yang, Q., X. Wu, 10 Challenging Problems in Data Mining Research, International Journal of Information Technology Decision Making, Vol. 5, No. 4, 2006, pp. 597–604.

CHAPTER 11

Akerkar, R., P. Lingras, Building an Intelligent Web: Theory and Practice, Jones and Bartlett Publishers, Sudbury, MA, 2008.

Chang, G., M. J. Haeley, J. A. M. McHugh, J. T. L. Wang, Mining the World Wide Web: An Information Search Approach, Kluwer Academic Publishers, Boston, MA, 2001.

Fan, F., L. Wallace, S. Rich, Z. Zhang, Tapping the Power of Text Mining, Communications of ACM, Vol. 49, No. 9, 2006, pp. 76–82.

Garcia, E., SVD and LSI Tutorial 4: Latent Semantic Indexing (LSI) How-to Calculations, Mi Islita, 2006, http://www.miislita.com/information-retrieval-tutorial/svd-lsi-tutorial-4-lsi-how-to-calculations.html.

Han, J., M. Kamber, Data Mining: Concepts and Techniques, 2nd edition, San Francisco, Morgan Kaufmann, 2006.

Jackson, P., I. Moulinier, Natural Language Processing for Online Applications: Text Retrieval, Extraction and Categorization, John Benjamins Publ. Co., Amsterdam, 2007.

Langville, A. N., C. D. Meyer, Google’s PageRank and Beyond: The Science of Search Engine Rankings, Princeton University Press, Princeton, 2006.

Liu, B., Web Data Mining: Exploring Hyperlinks, Contents and Usage Data, Springer, Heidelberg, 2007.

Mulvenna, M. D., et al., eds., Personalization on the Net Using Web Mining, CACM, Vol. 43, No. 8, 2000.

Nisbet, R., J. Elder, G. Miner, Advanced Algorithms for Data Mining, in Handbook of Statistical Analysis and Data Mining Applications, R. Nisbet, J. Elder, J. F. Elder, G. Miner, eds., Academic Press, Amsterdam, NL, 2009, pp. 151–172.

Sirmakessis, S., Text Mining and Its Applications, Springer-Verlag, Berlin, 2003.

Zhang, Q., R. S. Segall, Review of Data, Text and Web Mining Software, Kybernetes, Vol. 39, No. 4, 2010, pp. 625–655.

Zhang, Y., et al., Computational Web Intelligence: Intelligent Technology for Web Applications, World Scientific Publ. Co., Singapore, 2004.

Zhang, X., J. Edwards, J. Harding, Personalised Online Sales Using Web Usage Data Mining, Computers in Industry, Vol. 58, No. 8–9, 2007, pp. 772–782.

CHAPTER 12

Antunes, C., A. Oliveira, Temporal Data Mining: An Overview, Proceedings of Workshop on Temporal Data Mining (KDD'01). 2001, pp. 1–13.

Bar-Or, A., R. Wolff, A. Schuster, D. Keren, Decision Tree Induction in High Dimensional, Hierarchically Distributed Databases, Proceedings of 2005 SIAM International Conference on Data Mining (SDM’05), Newport Beach, CA, April 2005.

Basak, J., R. Kothari, A Classification Paradigm for Distributed Vertically Partitioned Data, Neural Computation, Vol. 16, No. 7, 2004, pp. 1525–1544.

Bhaduri, K., R. Wolff, C. Giannella, H. Kargupta, Distributed Decision-Tree Induction in Peer-to-Peer Systems, Statistical Analysis and Data Mining, Vol. 1, No. 2, 2008, pp. 85–103.

Bishop, C. M., Pattern Recognition and Machine Learning, Springer, New York, 2006.

Branch, J., B. Szymanski, R. Wolff, C. Gianella, H. Kargupta, In-network Outlier Detection in Wireless Sensor Networks, Proceedings of the 26th International Conference on Distributed Computing Systems (ICDCS), July 2006, pp. 102–111.

Cannataro, M., D. Talia, The Knowledge Grid, Communications of the ACM, Vol. 46, No. 1, 2003, pp. 89–93.

Cios, K. J., W. Pedrycz, R. W. Swiniarski, L. A. Kurgan, Data Mining: A Knowledge Discovery Approach, Springer, New York, 2007.

Congiusta, A., D. Talia, P. Trunfio, Service-Oriented Middleware for Distributed Data Mining on the Grid, Journal of Parallel and Distributed Computing, Vol. 68, No. 1, 2008, pp. 3–15.

Copp, C., Data Mining and Knowledge Discovery Techniques, Defence Today, NCW 101, 2008, http://www.ausairpower.net/NCW-101-17.pdf.

Datta, S., K. Bhaduri, C. Giannella, R. Wolff, H. Kargupta, Distributed Data Mining in Peer-to-Peer Networks, IEEE Internet Computing, Vol. 10, No. 4, 2006, pp. 18–26.

Ester, M., H.-P. Kriegel, J. Sander, Spatial Data Mining: A Database Approach, Proceedings of 5th International Symposium on Advances in Spatial Databases, 1997, pp. 47–66.

Faloutsos, C., Mining Time Series Data, Tutorial ICML 2003, Washington, DC, August 2003.

Fuchs, E., T. Gruber, J. Nitschke, B. Sick, On-Line Motif Detection in Time Series with Swift Motif, Pattern Recognition, Vol. 42, 2009, pp. 3015–3031.

Gorodetsky, V., O. Karsaeyv, V. Samoilov, Software Tool for Agent Based Distributed Data Mining, International Conference on Integration of Knowledge Intensive Multi-Agent Systems (KIMAS), Boston, MA, October 2003.

Guo, H., W. Hsu, A Survey of Algorithms for Real-Time Bayesian Network Inference, AAAI-02/KDD-02/UAI-02 Workshop on Real-Time Decision Support and Diagnosis, 2002.

Hammouda, K., M. Kamel, HP2PC: Scalable Hierarchically-Distributed Peer-to-Peer Clustering, Proceedings of the 2007 SIAM International Conference on Data Mining (SDM ’07), Philadelphia, PA, 2007.

Januzaj, E., et al., Towards Effective and Efficient Distributed Clustering, Proceedings of the ICDM 2003 Conference, Florida, 2003.

Keogh, E., Data Mining and Machine Learning in Time Series Databases, Tutorial ECML/PKDD 2003, Cavtat-Dubrovnik (Croatia), September 2003.

Koperski, K., et al., Spatial Data Mining: Progress and Challenges, SIGMOD’96 Workshop on Research Issues on Data Mining and Knowledge Discovery, 1996.

Kotecha, J. H., V. Ramachandran, A. M. Sayeed, Distributed Multitarget Classification in Wireless Sensor Networks, IEEE Journal of Selected Areas in Communications, Vol. 23, No. 4, 2005, pp. 703–713.

Kriegel, H. P., et al., Future Trends in Data Mining, Data Mining and Knowledge Discovery, Vol. 15, 2007, pp. 87–97.

Kumar, A., M. Kantardzic, S. Madden, Guest Editors, Introduction: Distributed Data Mining–Framework and Implementations, IEEE Internet Computing, Vol. 10, No. 4, 2006, pp. 15–17.

Lavrac, N., et al., Introduction: Lessons Learned from Data Mining Applications and Collaborative Problem Solving, Machine Learning, Vol. 57, 2004, pp. 13–34.

Laxman, S., P. S. Sastry, A Survey of Temporal Data Mining, Sadhana, Vol. 31, No. 2, 2006, pp. 173–198.

Li, T., S. Zhu, M. Ogihara, Algorithms for Clustering High Dimensional and Distributed Data, Intelligent Data Analysis Journal, Vol. 7, No. 4, 2003.

Li, S., T. Wu, W. M. Pottenger, Distributed Higher Order Association Rule Mining Using Information Extracted from Textual Data, SIGKDD Exploration, Vol. 7, No. 1, 2005, pp. 26–35.

Liu, K., H. Kargupta, J. Ryan, Random Projection-Based Multiplicative Data Perturbation for Privacy Preserving Distributed Data Mining, IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 18, No. 1, 2006, pp. 92–106.

Miller, H. J., Geographic Data Mining and Knowledge Discovery, in Handbook of Geographic Information Science”,