SIGKDD 2000 - PDF Preprint Papers

SIGKDD 2000

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SIGKDD
2000

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The UCI KDD Archive of Large Data Sets for Data Mining Research and Experimentation

13 years 4 months ago

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Advances in data collection and storage have allowed organizations to create massive, complex and heterogeneous databases, which have stymied traditional methods of data analysis....

Stephen D. Bay, Dennis F. Kibler, Michael J. Pazza...

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Id	Views	Title	Status

1	237	The UCI KDD Archive of Large Data Sets for Data Mining Research and Experimentation	claim
2	231	KDD-99 Classifier Learning Contest: LLSoft's Results Overview	claim
3	150	KDD-Cup 2000 Organizers' Report: Peeling the Onion	claim
4	139	Support Vector Machines: Hype or Hallelujah?	claim
5	130	KDD-Cup 99: Knowledge Discovery In a Charitable Organization's Donor Database	claim
6	121	Data Snooping, Dredging and Fishing: The Dark Side of Data Mining, A SIGKDD99 Panel Report	claim
7	112	Artificial Neural Networks - A Science in Trouble	claim
8	112	Profiling your Customers using Bayesian Networks	claim
9	109	Report on WebDB'2000: 3rd International Workshop on the Web and Databases	claim
10	106	Data Mining Models as Services on the Internet	claim
11	106	Data mining for hypertext: A tutorial survey	claim
12	103	Interface '99: A Data Mining Overview	claim
13	96	Phenomenal Data Mining: From Data to Phenomena	claim
14	96	The MP13 Approach to the KDD'99 Classifier Learning Contest	claim
15	95	Scalability for Clustering Algorithms Revisited	claim
16	95	Web Usage Mining: Discovery and Applications of Usage Patterns from Web Data	claim
17	92	WEBKDD 2000 - Web Mining for E-Commerce	claim
18	90	Distributed Data Clustering Can Be Efficient and Exact	claim
19	89	Winning the KDD99 Classification Cup: Bagged Boosting	claim
20	89	Measuring Lift Quality in Database Marketing	claim
21	87	Integrating Data Mining into Vertical Solutions	claim
22	85	Mining Frequent Patterns with Counting Inference	claim
23	84	Results of the KDD'99 Classifier Learning	claim
24	75	KDD-99: The Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining	claim
25	75	Mining Patterns in Long Sequential Data with Noise	claim
26	73	A note on "Beyond Market Baskets: Generalizing Association Rules to Correlations"	claim
27	70	The Segment Support Map: Scalable Mining of Frequent Itemsets	claim
28	69	WebKDD-99: Workshop on Web Usage Analysis and User Profiling	claim
29	68	KDD'99 Competition: Knowledge Discovery Contest	claim
30	67	Algorithms for Association Rule Mining - A General Survey and Comparison	claim
31	66	Scalable Data Mining with Model Constraints	claim
32	62	A Fine Grained Heuristic to Capture Web Navigation Patterns	claim
33	60	Systems Support for Scalable Data Mining	claim
34	57	Theoretical Frameworks for Data Mining	claim

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