| 书目名称 | Scalable Processing of Spatial-Keyword Queries |
| 编辑 | Ahmed R. Mahmood,Walid G. Aref |
| 视频video | http://file.papertrans.cn/862/861044/861044.mp4 |
| 丛书名称 | Synthesis Lectures on Data Management |
| 图书封面 |  |
| 描述 | .Text data that is associated with location data has become ubiquitous. A tweet is an example of this type of data, where the text in a tweet is associated with the location where the tweet has been issued. We use the term spatial-keyword data to refer to this type of data. Spatial-keyword data is being generated at massive scale. Almost all online transactions have an associated spatial trace. The spatial trace is derived from GPS coordinates, IP addresses, or cell-phone-tower locations. Hundreds of millions or even billions of spatial-keyword objects are being generated daily. Spatial-keyword data has numerous applications that require efficient processing and management of massive amounts of spatial-keyword data...This book starts by overviewing some important applications of spatial-keyword data, and demonstrates the scale at which spatial-keyword data is being generated. Then, it formalizes and classifies the various types of queries that execute over spatial-keyword data.Next, it discusses important and desirable properties of spatial-keyword query languages that are needed to express queries over spatial-keyword data. As will be illustrated, existing spatial-keyword query la |
| 出版日期 | Book 2019 |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-031-01867-1 |
| isbn_softcover | 978-3-031-00739-2 |
| isbn_ebook | 978-3-031-01867-1Series ISSN 2153-5418 Series E-ISSN 2153-5426 |
| issn_series | 2153-5418 |
| copyright | Springer Nature Switzerland AG 2019 |
|Archiver|手机版|小黑屋|
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