KDD 2003 - PDF Preprint Papers

KDD 2003 International Conference on Knowledge Discovery and Data Mining

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KDD
2003
ACM

449views Data Mining» more KDD 2003»

Passenger-based predictive modeling of airline no-show rates

15 years 25 days ago

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Airlines routinely overbook flights based on the expectation that some fraction of booked passengers will not show for each flight. Accurate forecasts of the expected number of no...

Richard D. Lawrence, Se June Hong, Jacques Cherrie...

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Id	Views	Title	Status

1	449	Passenger-based predictive modeling of airline no-show rates	claim
2	269	Maximizing the spread of influence through a social network	claim
3	266	Applying data mining in investigating money laundering crimes	claim
4	243	Accurate decision trees for mining high-speed data streams	claim
5	233	SEWeP: using site semantics and a taxonomy to enhance the Web personalization process	claim
6	217	Algorithms for estimating relative importance in networks	claim
7	214	Adaptive duplicate detection using learnable string similarity measures	claim
8	210	Privacy-preserving k-means clustering over vertically partitioned data	claim
9	205	The data mining approach to automated software testing	claim
10	205	CloseGraph: mining closed frequent graph patterns	claim
11	195	Visualizing changes in the structure of data for exploratory feature selection	claim
12	194	Finding recent frequent itemsets adaptively over online data streams	claim
13	192	Efficient elastic burst detection in data streams	claim
14	191	Assessment and pruning of hierarchical model based clustering	claim
15	190	Distance-enhanced association rules for gene expression	claim
16	180	Classifying large data sets using SVMs with hierarchical clusters	claim
17	177	CLOSET+: searching for the best strategies for mining frequent closed itemsets	claim
18	175	Correlating synchronous and asynchronous data streams	claim
19	175	Weighted Association Rule Mining using weighted support and significance framework	claim
20	175	Time and sample efficient discovery of Markov blankets and direct causal relations	claim
21	170	Efficient decision tree construction on streaming data	claim
22	162	Improving spatial locality of programs via data mining	claim
23	161	Empirical Bayesian data mining for discovering patterns in post-marketing drug safety	claim
24	161	Eliminating noisy information in Web pages for data mining	claim
25	160	Playing hide-and-seek with correlations	claim
26	157	Cross-training: learning probabilistic mappings between topics	claim
27	156	Mining distance-based outliers in near linear time with randomization and a simple pruning rule	claim
28	156	Fast vertical mining using diffsets	claim
29	155	Graph-based anomaly detection	claim
30	152	An adaptive nearest neighbor search for a parts acquisition ePortal	claim
31	152	Interactive exploration of coherent patterns in time-series gene expression data	claim
32	150	Learning relational probability trees	claim
33	149	Knowledge-based data mining	claim
34	148	A highly-usable projected clustering algorithm for gene expression profiles	claim
35	148	Mining data records in Web pages	claim
36	148	Mining concept-drifting data streams using ensemble classifiers	claim
37	146	Style mining of electronic messages for multiple authorship discrimination: first results	claim
38	146	Probabilistic discovery of time series motifs	claim
39	145	Evidence combination in biomedical natural-language processing	claim
40	145	Carpenter: finding closed patterns in long biological datasets	claim
41	144	Clinical and financial outcomes analysis with existing hospital patient records	claim
42	143	To buy or not to buy: mining airfare data to minimize ticket purchase price	claim
43	142	Extracting information from text and images for location proteomics	claim
44	142	Frequent-subsequence-based prediction of outer membrane proteins	claim
45	142	Mining phenotypes and informative genes from gene expression data	claim
46	140	Mining hepatitis data with temporal abstraction	claim
47	135	Efficiently handling feature redundancy in high-dimensional data	claim
48	133	Interactive Analysis of Gene Interactions Using Graphical gaussian model	claim
49	133	PROXIMUS: a framework for analyzing very high dimensional discrete-attributed datasets	claim
50	132	PaintingClass: interactive construction, visualization and exploration of decision trees	claim
51	130	Towards systematic design of distance functions for data mining applications	claim
52	130	Distributed multivariate regression based on influential observations	claim
53	129	Online novelty detection on temporal sequences	claim
54	129	Nantonac collaborative filtering: recommendation based on order responses	claim
55	129	Empirical comparisons of various voting methods in bagging	claim
56	128	Similarity analysis on government regulations	claim
57	127	Experiments with random projections for machine learning	claim
58	127	Towards NIC-based intrusion detection	claim
59	124	Information-theoretic co-clustering	claim
60	122	Enhanced visualization of time series through higher fourier harmonics	claim
61	122	Understanding captions in biomedical publications	claim
62	122	Natural communities in large linked networks	claim
63	122	Discovery of climate indices using clustering	claim
64	120	Distributed cooperative mining for information consortia	claim
65	120	On detecting differences between groups	claim
66	118	Generating English summaries of time series data using the Gricean maxims	claim
67	116	Golden Path Analyzer: using divide-and-conquer to cluster Web clickstreams	claim
68	116	XRules: an effective structural classifier for XML data	claim
69	114	Information awareness: a prospective technical assessment	claim
70	113	Using randomized response techniques for privacy-preserving data mining	claim
71	113	Indexing multi-dimensional time-series with support for multiple distance measures	claim
72	113	Mining unexpected rules by pushing user dynamics	claim
73	112	Screening and interpreting multi-item associations based on log-linear modeling	claim
74	111	Translation-invariant mixture models for curve clustering	claim
75	111	Critical event prediction for proactive management in large-scale computer clusters	claim
76	109	Generative model-based clustering of directional data	claim
77	109	Experimental design for solicitation campaigns	claim
78	108	Aggregation-based feature invention and relational concept classes	claim
79	99	Fragments of order	claim
80	97	Reducing large diagonals in kernel matrices through semidefinite programming	claim

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