Lam, W., & Segre, A. M. (1997). Distributed data mining of probabilistic knowledge. ICDCS. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
Distributed Clustering Using Collective Principal.. - Kargupta, Huang.. (2001) (11 citations) (Correct)
....storage, access, and analysis. The ability of various organizations to collect, store, and retrieve huge amounts of data has necessitated the development of algorithms that can extract useful information from these databases. KDD addresses this issue. Distributed knowledge discovery (DKD) [10, 13, 20, 22, 25, 32, 37, 50, 55] takes KDD to a new platform. It embraces the growing trend of merging computation with communication and explores all facets of the KDD process in the context of the emerging distributed computing environments. DKD accepts the fact that data may be inherently distributed among di erent loosely ....
W. Lam and A. M. Segre. Distributed data mining of probabilistic knowledge. In Proceedings of the 17th International Conference on Distributed Computing Systems, pages 178-185, Washington, 1997. IEEE Computer Society Press.
Collective Data Mining: A New Perspective Toward.. - Kargupta, Byung-Hoon, al (1999) (20 citations) (Correct)
....approach to mining classi ers from distributed data sources is suggested by [9] In this method, a single, best, rule is generated in each distributed data source. These rules are then ranked using some criterion and some number of the top ranked rules are selected to form the rule set. In [26] the authors report a technique to automatically produce a Bayesian belief network from discovered knowledge using a distributed approach. The PADMA system [19, 18] also deals with the problem of distributed data mining from homogeneous data sites. This system implemented a distributed clustering ....
W. Lam and A. M. Segre. Distributed data mining of probabilistic knowledge. In Proceedings of the 17th International Conference on Distributed Computing Systems, pages 178-185, Washington, 1997. IEEE Computer Society Press.
Collective Data Mining: A New Perspective Toward Distributed.. - Kargupta, al (1999) (20 citations) (Correct)
....mining classifiers from distributed data sources is suggested by (Cho Wuthrich, 1998) In this method, a single, best, rule is generated in each distributed data source. These rules are then ranked using some criterion and some number of the top ranked rules are selected to form the rule set. In (Lam Segre, 1997) the authors extend efforts to automatically produce a Bayesian belief network from discovered knowledge by developing a distributed approach to this exponential time problem. A formal treatment of distributed databases is presented in (Nowak, 1998) The author assets that the information ....
Lam, W., & Segre, A. M. (1997). Distributed data mining of probabilistic knowledge. In Proceedings of the 17th International Conference on Distributed Computing Systems (pp. 178--185). Washington: IEEE Computer Society Press.
Distributed Multivariate Regression Using Wavelet-based.. - Hershberger, Kargupta (1999) (2 citations) (Correct)
....mining classifiers from distributed data sources is suggested by (Cho Wuthrich, 1998) In this method, a single, best, rule is generated in each distributed data source. These rules are then ranked using some criterion and some number of the top ranked rules are selected to form the rule set. In (Lam Segre, 1997) the authors extend efforts to automatically produce a Bayesian belief network from discovered knowledge by developing a distributed approach to this exponential time problem. In (Yamanishi, 1997) the author presents two models of distributed Bayesian learning. Both models employ distributed agent ....
Lam, W., & Segre, A. M. (1997). Distributed data mining of probabilistic knowledge. In Proceedings of the 17th International Conference on Distributed Computing Systems (pp. 178--185). Washington: IEEE Computer Society Press.
The Collective Data Mining: A Technology For Ubiquitous Data.. - Kargupta, Park (1998) (1 citation) (Correct)
....The meta learning (Chan Stolfo, 1993) based JAM system, the PADMA system (Kargupta et al. 1996) the WoRLD system (Aronis, Kolluri, Provost, Buchanan, 1996) the BODHI system (Kargupta et al. 1998) are some examples of DDM systems. Additional DDM related work may be found elsewhere (Lam Segre, 1997; Nowak, 1998) A typical application domain of DDM either has inherently distributed data sources or centralized data partitioned at different sites. The data sites may be homogeneous, i.e. each site stores data for exactly the same set of features. However, for most of the interesting DDM ....
Lam, W., & Segre, A. M. (1997). Distributed data mining of probabilistic knowledge. In Proceedings of the 17th International Conference on Distributed Computing Systems (pp. 178--185).
Collective Data Mining From Distributed.. - Kargupta.. (1998) (1 citation) (Correct)
....classifiers from distributed data sources is suggested by (Cho W uthrich 1998) In this method, a single, best, rule is generated in each distributed data source. These rules are then ranked using some criterion and some number of the top ranked rules are selected to form the rule set. In (Lam Segre 1997) the authors extend efforts to automatically produce a Bayesian belief network from discovered knowledge by developing a distributed approach to this exponential time problem. A formal treatment of distributed databases is presented in (Nowak 1998) The author assets that the information contained ....
Lam, W., and Segre, A. M. 1997. Distributed data mining of probabilistic knowledge. In Proceedings of the 17th International Conference on Distributed Computing Systems, 178--185. Washington: IEEE Computer Society Press.
A New Distributed Data Mining Model Based on Similarity - Tao Li Computer (2003) (1 citation) (Correct)
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Lam, W., & Segre, A. M. (1997). Distributed data mining of probabilistic knowledge. ICDCS.
Distributed Data Mining Bibliography - Hillol (Correct)
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W. Lam and A. M. Segre. Distributed Data Mining of Probabilistic Knowledge. In Proceedings of the 17th International Conference on Distributed Computing Systems, pages 178--185, Washington, DC, 1997. IEEE Computer Society Press.
Distributed Clustering Using Collective Principal.. - Kargupta, Huang.. (1999) (11 citations) (Correct)
No context found.
W. Lam and A. M. Segre. Distributed data mining of probabilistic knowledge. In Proceedings of the 17th International Conference on Distributed Computing Systems, pages 178-185, Washington, 1997. IEEE Computer Society Press.
Unsupervised Distributed Clustering - Tasoulis, Vrahatis (2004) (Correct)
No context found.
W. Lam and A.M. Segre. Distributed data mining of probabilistic knowledge. In Proceedings of the 17th International Conference on Distributed Computing Systems, Washington, pages 178--185. IEEE Computer Society Press, 1997.
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