Querying and mining uncertain data streams:
"Data uncertainty widely exists in many applications, and an uncertain data stream is a series of uncertain tuples that arrive rapidly. However, traditional techniques for deterministic data streams cannot be applied to deal with data uncertainty directly due to the exponential growth of possib...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Singapore
World Scientific Publishing Co. Pte. Ltd.
c2016
|
| Schriftenreihe: | East China Normal University scientific reports
volume 3 |
| Schlagworte: | |
| Online-Zugang: | FHN01 Volltext |
| Zusammenfassung: | "Data uncertainty widely exists in many applications, and an uncertain data stream is a series of uncertain tuples that arrive rapidly. However, traditional techniques for deterministic data streams cannot be applied to deal with data uncertainty directly due to the exponential growth of possible solution space. "This book provides a comprehensive overview of the authors' work on querying and mining uncertain data streams. Its contents include some important discoveries dealing with typical topics such as top-k query, ER-Topk query, rarity estimation, set similarity, and clustering. Querying and Mining Uncertain Data Streams is written for professionals, researchers, and graduate students in data mining and its various related fields. Contents: Introduction; Queries Over the Sliding-window Model ; Query Over the Landmark Model ; Rarity Estimation ; Set similarity; Clustering; Conclusion. Readership: Students and Professionals involved in data mining, big data, and data gathering. Key Features: The first book on uncertain data stream management. There exist significant contributions on typical topics."-- |
| Beschreibung: | Title from PDF file title page (viewed June 16, 2016) |
| Beschreibung: | 1 online resource (xvi, 148 p.) |
| ISBN: | 9789813142916 |
Internformat
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Datensatz im Suchindex
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| author | Jin, Cheqing |
| author_facet | Jin, Cheqing |
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| author_sort | Jin, Cheqing |
| author_variant | c j cj |
| building | Verbundindex |
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| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
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| dewey-search | 006.3/12 |
| dewey-sort | 16.3 212 |
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| id | DE-604.BV044637324 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:57:51Z |
| institution | BVB |
| isbn | 9789813142916 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030035295 |
| oclc_num | 988732478 |
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| owner | DE-92 |
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| physical | 1 online resource (xvi, 148 p.) |
| psigel | ZDB-124-WOP ZDB-124-WOP FHN_PDA_WOP |
| publishDate | 2016 |
| publishDateSearch | 2016 |
| publishDateSort | 2016 |
| publisher | World Scientific Publishing Co. Pte. Ltd. |
| record_format | marc |
| series2 | East China Normal University scientific reports |
| spelling | Jin, Cheqing Verfasser aut Querying and mining uncertain data streams Cheqing Jin & Aoying Zhou Singapore World Scientific Publishing Co. Pte. Ltd. c2016 1 online resource (xvi, 148 p.) txt rdacontent c rdamedia cr rdacarrier East China Normal University scientific reports volume 3 Title from PDF file title page (viewed June 16, 2016) "Data uncertainty widely exists in many applications, and an uncertain data stream is a series of uncertain tuples that arrive rapidly. However, traditional techniques for deterministic data streams cannot be applied to deal with data uncertainty directly due to the exponential growth of possible solution space. "This book provides a comprehensive overview of the authors' work on querying and mining uncertain data streams. Its contents include some important discoveries dealing with typical topics such as top-k query, ER-Topk query, rarity estimation, set similarity, and clustering. Querying and Mining Uncertain Data Streams is written for professionals, researchers, and graduate students in data mining and its various related fields. Contents: Introduction; Queries Over the Sliding-window Model ; Query Over the Landmark Model ; Rarity Estimation ; Set similarity; Clustering; Conclusion. Readership: Students and Professionals involved in data mining, big data, and data gathering. Key Features: The first book on uncertain data stream management. There exist significant contributions on typical topics."-- Data mining Querying (Computer science) Uncertainty (Information theory) Zhou, Aoying 1965- Sonstige oth http://www.worldscientific.com/worldscibooks/10.1142/10009#t=toc Verlag URL des Erstveroeffentlichers Volltext |
| spellingShingle | Jin, Cheqing Querying and mining uncertain data streams Data mining Querying (Computer science) Uncertainty (Information theory) |
| title | Querying and mining uncertain data streams |
| title_auth | Querying and mining uncertain data streams |
| title_exact_search | Querying and mining uncertain data streams |
| title_full | Querying and mining uncertain data streams Cheqing Jin & Aoying Zhou |
| title_fullStr | Querying and mining uncertain data streams Cheqing Jin & Aoying Zhou |
| title_full_unstemmed | Querying and mining uncertain data streams Cheqing Jin & Aoying Zhou |
| title_short | Querying and mining uncertain data streams |
| title_sort | querying and mining uncertain data streams |
| topic | Data mining Querying (Computer science) Uncertainty (Information theory) |
| topic_facet | Data mining Querying (Computer science) Uncertainty (Information theory) |
| url | http://www.worldscientific.com/worldscibooks/10.1142/10009#t=toc |
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