Results 61 to 70 of about 80,307 (206)
Modelling Stabilometric Time Series
, 2010 Stabilometry is a branch of medicine that studies balance-related human functions. Stabilometric systems generate time series. The analysis of these time series using data mining techniques can be very useful for domain experts.
Caraça-Valente Hernández, Juan Pedro +3 more
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Similarity Measure Based on Incremental Warping Window for Time Series Data Mining
IEEE Access, 2019 A similarity measure is one of the most important tasks in the fields of time series data mining. Its quality often affects the efficiency and effectiveness of the related algorithms that need to measure the similarity between two time series in advance.
Hailin Li, Cheng Wang
doaj +1 more source
Research on Domain-Driven Time Series Data Mining Techniques
, 2012 計畫編號：NSC100-2221-E032-065 研究期間：20110801~20120731 研究經費：450,000時間序列是指每隔一定時間將所觀察的目標記錄而成的資料。故在日常生活中， 有許多現象都可以視為時間序列資料，因此，在時間序列上亦發展了許多不同的研究 議題與成果。然而，現有的演算法皆屬於資料衍生的時間序列資料探勘技術，而其主 要缺點即是探勘後的資訊皆需經過專家進一步分析後方能運用。所以，近幾年興起了 領域衍生的資料探勘概念。可惜的是，截至目前為止，所有的時間序列探勘文獻都屬 ...
陳俊豪
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Carbon footprint forecasting using time series data mining methods: the case of Turkey. [PDF]
Environ Sci Pollut Res Int, 2021 Akyol M, Uçar E.
europepmc +1 more source
The contribution of data mining to information science
, 2004 The information explosion is a serious challenge for current information institutions. On the other hand, data mining, which is the search for valuable information in large volumes of data, is one of the solutions to face this challenge.
Liu, X +3 more
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Towards Robust and Privacy-aware Time Series Data Mining
, 2023 With the advancement of sensor technology, large volumes of high-resolution time series are collected in a variety of domains and data mining in large-scale time series has attracted great research attention. While many time series data mining methods in
Zhang, Li
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Learning short multivariate time series models through evolutionary and sparse matrix computation
, 2005 Multivariate time series (MTS) data are widely available in different fields including medicine, finance, bioinformatics, science and engineering. Modelling MTS data accurately is important for many decision making activities.
Liu, X, Kok, J, Swift, S
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Review of Outlier Detection Algorithms [PDF]
Jisuanji kexueOutlier detection,as an important research direction in the field of data mining,aims to discover data points in a dataset that are different from the majority and have potential analytical value,assistresearchers in identifying potential issues in the ...
KONG Lingchao, LIU Guozhu
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Study on Visual Techniques of Potential Pattern Discovery for Time Series Data
MATEC Web of Conferences, 2018 Sequential pattern mining is always a very important branch of time series data mining. The pattern mining with visual means can be used to extract the knowledge of time series data more intuitively. Based on the research content, this paper analyzes the
Xu Dalin, Wei Yingmei
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An Efficient Algorithm for Frequent Pattern Mining for Real-Time Business Intelligence Analytics in Dense Datasets [PDF]
Finding frequent patterns from databases has been the most time consuming process in data mining tasks, like association rule mining. Frequent pattern mining in real-time is of increasing thrust in many business applications such as e-commerce ...
Dass, Rajanish
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