Search Results - "Keogh, Eamonn"

Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress by Wu, Renjie, Keogh, Eamonn J.

“…Time series anomaly detection has been a perennially important topic in data science, with papers dating back to the 1950s. However, in recent years there has…”
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The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances by Bagnall, Anthony, Lines, Jason, Bostrom, Aaron, Large, James, Keogh, Eamonn

“…In the last 5 years there have been a large number of new time series classification algorithms proposed in the literature. These algorithms have been…”
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FastDTW is approximate and Generally Slower than the Algorithm it Approximates by Wu, Renjie, Keogh, Eamonn J.

“…Many time series data mining problems can be solved with repeated use of distance measure. Examples of such tasks include similarity search, clustering,…”
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When is Early Classification of Time Series Meaningful? by Wu, Renjie, Der, Audrey, Keogh, Eamonn J.

“…Since its introduction two decades ago, there has been increasing interest in the problem of early classification of time series . This problem generalizes…”
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Generalizing DTW to the multi-dimensional case requires an adaptive approach by Shokoohi-Yekta, Mohammad, Hu, Bing, Jin, Hongxia, Wang, Jun, Keogh, Eamonn

“…In recent years Dynamic Time Warping (DTW) has emerged as the distance measure of choice for virtually all time series data mining applications. For example,…”
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The UCR time series archive by Dau, Hoang Anh, Bagnall, Anthony, Kamgar, Kaveh, Yeh, Chin-Chia Michael, Zhu, Yan, Gharghabi, Shaghayegh, Ratanamahatana, Chotirat Ann, Keogh, Eamonn

“…The UCR time series archive–introduced in 2002, has become an important resource in the time series data mining community, with at least one thousand published…”
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Parasitic mites alter chicken behaviour and negatively impact animal welfare by Murillo, Amy C., Abdoli, Alireza, Blatchford, Richard A., Keogh, Eamonn J., Gerry, Alec C.

“…The northern fowl mite, Ornithonyssus sylviarum , is one of the most common and damaging ectoparasites of poultry. As an obligate blood feeding mite, the…”
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CID: an efficient complexity-invariant distance for time series by Batista, Gustavo E. A. P. A., Keogh, Eamonn J., Tataw, Oben Moses, de Souza, Vinícius M. A.

“…The ubiquity of time series data across almost all human endeavors has produced a great interest in time series data mining in the last decade. While dozens of…”
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On the Need for Time Series Data Mining Benchmarks: A Survey and Empirical Demonstration by Keogh, Eamonn, Kasetty, Shruti

“…Issue Title: Special Issue: Selected Papers from the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining --Part II In the last…”
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Faster and more accurate classification of time series by exploiting a novel dynamic time warping averaging algorithm by Petitjean, François, Forestier, Germain, Webb, Geoffrey I., Nicholson, Ann E., Chen, Yanping, Keogh, Eamonn

“…A concerted research effort over the past two decades has heralded significant improvements in both the efficiency and effectiveness of time series…”
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Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress (Extended Abstract) by Wu, Renjie, Keogh, Eamonn J.

“…Most of the time series anomaly detection papers tested on a handful of popular benchmark datasets, created by Yahoo [1], Numenta [2], NASA [3] or Pei's Lab…”
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When is Early Classification of Time Series Meaningful? (Extended Abstract) by Wu, Renjie, Der, Audrey, Keogh, Eamonn J.

“…The problem of early classification of time series (ETSC) generalizes classic time series classification to ask if we can classify a time series subsequence…”
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FastDTW is approximate and Generally Slower than the Algorithm it Approximates (Extended Abstract) by Wu, Renjie, Keogh, Eamonn J.

“…Many time series data mining problems can be solved with repeated use of distance measure. Examples of such tasks include similarity search, clustering,…”
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Experimental comparison of representation methods and distance measures for time series data by Wang, Xiaoyue, Mueen, Abdullah, Ding, Hui, Trajcevski, Goce, Scheuermann, Peter, Keogh, Eamonn

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Experiencing SAX: a novel symbolic representation of time series by Lin, Jessica, Keogh, Eamonn, Wei, Li, Lonardi, Stefano

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MDL-based time series clustering by Rakthanmanon, Thanawin, Keogh, Eamonn J., Lonardi, Stefano, Evans, Scott

“…Time series data are pervasive across all human endeavors, and clustering is arguably the most fundamental data mining application. Given this, it is somewhat…”
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Exploring Low Cost Laser Sensors to Identify Flying Insect Species: Evaluation of Machine Learning and Signal Processing Methods by Silva, Diego F., Souza, Vinícius M. A., Ellis, Daniel P. W., Keogh, Eamonn J., Batista, Gustavo E. A. P. A.

“…Insects have a close relationship with the humanity, in both positive and negative ways. Mosquito borne diseases kill millions of people and insect pests…”
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Supporting exact indexing of arbitrarily rotated shapes and periodic time series under Euclidean and warping distance measures by Keogh, Eamonn, Wei, Li, Xi, Xiaopeng, Vlachos, Michail, Lee, Sang-Hee, Protopapas, Pavlos

“…Shape matching and indexing is important topic in its own right, and is a fundamental subroutine in most shape data mining algorithms. Given the ubiquity of…”
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Introducing Mplots: scaling time series recurrence plots to massive datasets by Shahcheraghi, Maryam, Mercer, Ryan, Rodrigues, João Manuel de Almeida, Der, Audrey, Gamboa, Hugo Filipe Silveira, Zimmerman, Zachary, Mauck, Kerry, Keogh, Eamonn

“…Time series similarity matrices (informally, recurrence plots or dot-plots), are useful tools for time series data mining. They can be used to guide data…”
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Finding the most unusual time series subsequence: algorithms and applications by Keogh, Eamonn, Lin, Jessica, Lee, Sang-Hee, Herle, Helga Van

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