A Review on Data Stream Classification
At this present time, the significance of data streams cannot be denied as many researchers have placed their focus on the research areas of databases, statistics, and computer science. In fact, data streams refer to some data points sequences that are found in order with the potential to be non-bin...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IOP Publishing
2018
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/24879/1/Haneen_2018.pdf |
| _version_ | 1796993364473675776 |
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| author | A. A., Haneen Noraziah, Ahmad Mohd Helmy, Abd Wahab |
| author_facet | A. A., Haneen Noraziah, Ahmad Mohd Helmy, Abd Wahab |
| author_sort | A. A., Haneen |
| collection | UMP |
| description | At this present time, the significance of data streams cannot be denied as many researchers have placed their focus on the research areas of databases, statistics, and computer science. In fact, data streams refer to some data points sequences that are found in order with the potential to be non-binding, which is generated from the process of generating information in a manner that is not stationary. As such the typical tasks of searching data have been linked to streams of data that are inclusive of clustering, classification, and repeated mining of pattern. This paper presents several data stream clustering approaches, which are based on density, besides attempting to comprehend the function of the related algorithms; both semi-supervised and active learning, along with reviews of a number of recent studies. |
| first_indexed | 2024-03-06T12:32:53Z |
| format | Conference or Workshop Item |
| id | UMPir24879 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T12:32:53Z |
| publishDate | 2018 |
| publisher | IOP Publishing |
| record_format | dspace |
| spelling | UMPir248792023-11-08T02:22:29Z http://umpir.ump.edu.my/id/eprint/24879/ A Review on Data Stream Classification A. A., Haneen Noraziah, Ahmad Mohd Helmy, Abd Wahab Z665 Library Science. Information Science At this present time, the significance of data streams cannot be denied as many researchers have placed their focus on the research areas of databases, statistics, and computer science. In fact, data streams refer to some data points sequences that are found in order with the potential to be non-binding, which is generated from the process of generating information in a manner that is not stationary. As such the typical tasks of searching data have been linked to streams of data that are inclusive of clustering, classification, and repeated mining of pattern. This paper presents several data stream clustering approaches, which are based on density, besides attempting to comprehend the function of the related algorithms; both semi-supervised and active learning, along with reviews of a number of recent studies. IOP Publishing 2018 Conference or Workshop Item PeerReviewed pdf en cc_by http://umpir.ump.edu.my/id/eprint/24879/1/Haneen_2018.pdf A. A., Haneen and Noraziah, Ahmad and Mohd Helmy, Abd Wahab (2018) A Review on Data Stream Classification. In: Journal of Physics: Conference Series, 1st International Conference on Big Data and Cloud Computing (ICoBiC) 2017 , 25-27 November 2017 , Kuching, Sarawak, Malaysia. pp. 1-8., 1018 (012019). ISSN 1742-6596 https://doi.org/10.1088/1742-6596/1018/1/012019 |
| spellingShingle | Z665 Library Science. Information Science A. A., Haneen Noraziah, Ahmad Mohd Helmy, Abd Wahab A Review on Data Stream Classification |
| title | A Review on Data Stream Classification |
| title_full | A Review on Data Stream Classification |
| title_fullStr | A Review on Data Stream Classification |
| title_full_unstemmed | A Review on Data Stream Classification |
| title_short | A Review on Data Stream Classification |
| title_sort | review on data stream classification |
| topic | Z665 Library Science. Information Science |
| url | http://umpir.ump.edu.my/id/eprint/24879/1/Haneen_2018.pdf |
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