Data Mining_ Concepts and Techniques - Jiawei Han [385]
[Ber81] Bertin, J., Graphics and Graphic Information Processing. (1981) Walter de Gruyter, Berlin .
[Ber03] Berry, M.W., Survey of Text Mining: Clustering, Classification, and Retrieval. (2003) Springer, New York .
[Bez81] Bezdek, J.C., Pattern Recognition with Fuzzy Objective Function Algorithms. (1981) Plenum Press .
[BFOS84] Breiman, L.; Friedman, J.; Olshen, R.; Stone, C., Classification and Regression Trees. (1984) Wadsworth International Group .
[BFR98] Bradley, P.; Fayyad, U.; Reina, C., Scaling clustering algorithms to large databases, In: Proc. 1998 Int. Conf. Knowledge Discovery and Data Mining (KDD’98) New York. (Aug. 1998), pp. 9–15.
[BG04] Bhattacharya, I.; Getoor, L., Iterative record linkage for cleaning and integration, In: Proc. SIGMOD 2004 Workshop on Research Issues on Data Mining and Knowledge Discovery (DMKD’04) Paris, France. (June 2004), pp. 11–18.
[B-G05] Ben-Gal, I., Outlier detection, In: (Editors: Maimon, O.; Rockach, L.) Data Mining and Knowledge Discovery Handbook: A Complete Guide for Practitioners and Researchers Kluwer Academic. (2005).
[BGKW03] Bucila, C.; Gehrke, J.; Kifer, D.; White, W., DualMiner: A dual-pruning algorithm for itemsets with constraints, Data Mining and Knowledge Discovery 7 (2003) 241–272.
[BGMP03] Bonchi, F.; Giannotti, F.; Mazzanti, A.; Pedreschi, D., ExAnte: Anticipated data reduction in constrained pattern mining, In: Proc. 7th European Conf. Principles and Pratice of Knowledge Discovery in Databases (PKDD’03), Vol. 2838/2003 (Sept. 2003) Cavtat-Dubrovnik, Croatia, pp. 59–70.
[BGRS99] Beyer, K.S.; Goldstein, J.; Ramakrishnan, R.; Shaft, U., When is “nearest neighbor” meaningful? In: Proc. 1999 Int. Conf. Database Theory (ICDT’99) Jerusalem, Israel. (Jan. 1999), pp. 217–235.
[BGV92] Boser, B.; Guyon, I.; Vapnik, V.N., A training algorithm for optimal margin classifiers, In: Proc. Fifth Annual Workshop on Computational Learning Theory (1992) ACM Press, San Mateo, CA, pp. 144–152.
[Bis95] Bishop, C.M., Neural Networks for Pattern Recognition. (1995) Oxford University Press .
[Bis06] Bishop, C.M., Pattern Recognition and Machine Learning. (2006) Springer, New York .
[BJR08] Box, G.E.P.; Jenkins, G.M.; Reinsel, G.C., Time Series Analysis: Forecasting and Control. 4th ed. (2008) Prentice-Hall .
[BKNS00] Breunig, M.M.; Kriegel, H.-P.; Ng, R.; Sander, J., LOF: Identifying density-based local outliers, In: Proc. 2000 ACM-SIGMOD Int. Conf. Management of Data (SIGMOD’00) Dallas, TX. (May 2000), pp. 93–104.
[BL99] Berry, M.J.A.; Linoff, G., Mastering Data Mining: The Art and Science of Customer Relationship Management. (1999) John Wiley & Sons .
[BL04] Berry, M.J.A.; Linoff, G.S., Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management. (2004) John Wiley & Sons .
[BL09] Blei, D.; Lafferty, J., Topic models, In: (Editors: Srivastava, A.; Sahami, M.) Text Mining: Theory and Applications Taylor and Francis. (2009).
[BLC+03] Barbará, D.; Li, Y.; Couto, J.; Lin, J.-L.; Jajodia, S., Bootstrapping a data mining intrusion detection system, In: Proc. 2003 ACM Symp. on Applied Computing (SAC’03) Melbourne, FL. (March 2003).
[BM98] Blum, A.; Mitchell, T., Combining labeled and unlabeled data with co-training, In: Proc. 11th Conf. Computational Learning Theory (COLT’98) Madison, WI. (1998), pp. 92–100.
[BMAD06] Bakar, Z.A.; Mohemad, R.; Ahmad, A.; Deris, M.M., A comparative study for outlier detection techniques in data mining, In: Proc. 2006 IEEE Conf. Cybernetics and Intelligent Systems Bangkok, Thailand. (2006), pp. 1–6.
[BMS97] Brin, S.; Motwani, R.; Silverstein, C., Beyond market basket: Generalizing association rules to correlations, In: Proc. 1997 ACM-SIGMOD Int. Conf. Management of Data (SIGMOD’97) Tucson, AZ. (May 1997), pp. 265–276.
[BMUT97] Brin, S.; Motwani, R.; Ullman, J.D.; Tsur, S., Dynamic itemset counting and implication rules for market basket analysis, In: Proc. 1997 ACM-SIGMOD Int. Conf. Management of Data (SIGMOD’97) Tucson, AZ. (May 1997), pp. 255–264.
[BN92] Buntine, W.L.; Niblett, T., A further