Results 271 to 280 of about 825,885 (311)

Compression-based data mining of sequential data

Data Mining and Knowledge Discovery, 2007
The vast majority of data mining algorithms require the setting of many input parameters. The dangers of working with parameter-laden algorithms are twofold. First, incorrect settings may cause an algorithm to fail in finding the true patterns. Second, a perhaps more insidious problem is that the algorithm may report spurious patterns that do not ...
Eamonn J. Keogh, Stefano Lonardi, Chotirat Ann Ratanamahatana, Li Wei 0001, Sang-Hee Lee 0003, John C. Handley   +5 more
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Exploratory Sequential Data Analysis: Foundations

Human-Computer Interaction, 1994
Human-computer interaction (HCI) investigators must consider the sequential nature of interaction and must often weigh behavioral, cognitive, and social factors when studying and designing today's increasingly complex systems. In many cases, laboratory experimentation is inappropriate and formal modeling intractable; instead, observational data ...
Sanderson, PM, Fisher, C
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Sequential data processing design

IBM Systems Journal, 1963
This paper outlines a systematic method of designing a data processing tape system utilizing currently available types of equipment. Primary effort was devoted to obtaining a procedure which would approach an "optimal" system design. The method presented is an iterative procedure which tends to focus special attention on the critical system ...
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Markovian Models for Sequential Data

2015
What the reader should know to understand this chapter \(\bullet \) Bayes decision theory (Chap. 5). \(\bullet \) Lagrange multipliers and conditional optimization problems (Chap. 9). \(\bullet \) Probability and statistics (Appendix A).
CAMASTRA, Francesco, Vinciarelli, Alessandro   +1 more
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On Horn Axiomatizations for Sequential Data

2004
We propose a notion of deterministic association rules for ordered data. We prove that our proposed rules can be formally justified by a purely logical characterization, namely, a natural notion of empirical Horn approximation for ordered data which involves background Horn conditions; these ensure the consistency of the propositional theory obtained ...
José L. Balcázar, Gemma Casas-Garriga
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Similarity measures for sequential data

WIREs Data Mining and Knowledge Discovery, 2011
AbstractExpressive comparison of strings is a prerequisite for analysis of sequential data in many areas of computer science. However, comparing strings and assessing their similarity is not a trivial task and there exists several contrasting approaches for defining similarity measures over sequential data.
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Incremental Prediction for Sequential Data

2010
Ensemble methods of incremental prediction for sequences refer to learning from new reference data that become available after the model has already been created from a previously available data set. The main obstacle in the prediction of sequential values in the real environment with huge amount of data is the integration of knowledge stored in the ...
Tomasz Kajdanowicz, Przemyslaw Kazienko
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A Sequential Data Preprocessing Tool for Data Mining

2014
Sequential dataset is a collection of records written and read in sequential order. Information from the sequential dataset is very useful in understanding the sequential patterns and finally making an appropriate decision. However, generating of sequential dataset from log file is quite complicated and difficult. Therefore, in this study we proposed a
Zailani Abdullah, Tutut Herawan, Haruna Chiroma, Mustafa Mat Deris   +3 more
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Sequential Subspace Clustering via Temporal Smoothness for Sequential Data Segmentation

IEEE Transactions on Image Processing, 2018
This paper develops a novel sequential subspace clustering method for sequential data. Inspired by the state-of-the-art methods, ordered subspace clustering, and temporal subspace clustering, we design a novel local temporal regularization term based on the concept of temporal predictability.
Haijun Liu 0001, Jian Cheng 0003, Feng Wang 0015   +2 more
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Sequential Pattern Mining from Sequential Data

2009
Owing to the progress of computer and network environments, it is easy to collect data with time information such as daily business reports, weblog data, and physiological information. This is the context in which methods of analyzing data with time information have been studied.
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