A similarity measure for temporal pattern discovery in time series data generated by IoT
Internet of Things implicitly generates myriads of temporal data. Unlocking such temporal data becomes a huge concern. Discovery and prediction of repeating temporal patterns and understanding the underlying temporal trends is much more challenging in the case of time stamped temporal data. At prese...
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| Published in: | 2016 International Conference on Engineering & MIS (ICEMIS) pp. 1 - 4 |
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| Main Authors: | , , , |
| Format: | Conference Proceeding |
| Language: | English |
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IEEE
01-09-2016
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| Abstract | Internet of Things implicitly generates myriads of temporal data. Unlocking such temporal data becomes a huge concern. Discovery and prediction of repeating temporal patterns and understanding the underlying temporal trends is much more challenging in the case of time stamped temporal data. At present, existing approaches do not reveal seasonal patterns, emerging or diminishing patterns. Determining similar temporal patterns and unearthing eccentric patterns require an efficient dissimilarity measure. This research addresses the similarity measure for revealing similar temporal patterns from time series data generated by IoT. |
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| AbstractList | Internet of Things implicitly generates myriads of temporal data. Unlocking such temporal data becomes a huge concern. Discovery and prediction of repeating temporal patterns and understanding the underlying temporal trends is much more challenging in the case of time stamped temporal data. At present, existing approaches do not reveal seasonal patterns, emerging or diminishing patterns. Determining similar temporal patterns and unearthing eccentric patterns require an efficient dissimilarity measure. This research addresses the similarity measure for revealing similar temporal patterns from time series data generated by IoT. |
| Author | Kumar, Puligadda Veereswara Radhakrishna, Vangipuram Janaki, Vinjamuri Aljawarneh, Shadi |
| Author_xml | – sequence: 1 givenname: Shadi surname: Aljawarneh fullname: Aljawarneh, Shadi email: saaljawarneh@just.edu.jo organization: Software Eng. Dept., JUST, Irbid, Jordan – sequence: 2 givenname: Vangipuram surname: Radhakrishna fullname: Radhakrishna, Vangipuram email: vrkrishna2014@gmail.com organization: Inf. Technol. Dept., VNR VJIET, Hyderabad, India – sequence: 3 givenname: Puligadda Veereswara surname: Kumar fullname: Kumar, Puligadda Veereswara email: pvkumar58@gmail.com organization: Dept. of CSE, Osmania Univ., Hyderabad, India – sequence: 4 givenname: Vinjamuri surname: Janaki fullname: Janaki, Vinjamuri email: janakicse@yahoo.com organization: Dept. of CSE, Vaagdevi Eng. Coll., Warangal, India |
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| Snippet | Internet of Things implicitly generates myriads of temporal data. Unlocking such temporal data becomes a huge concern. Discovery and prediction of repeating... |
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| SubjectTerms | association pattern seasonal pattern support bounds temporal data temporal trend time stamp |
| Title | A similarity measure for temporal pattern discovery in time series data generated by IoT |
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