| 書目名稱 | Preference-based Spatial Co-location Pattern Mining | | 編輯 | Lizhen Wang,Yuan Fang,Lihua Zhou | | 視頻video | http://file.papertrans.cn/755/754628/754628.mp4 | | 概述 | Provides a systematic, mathematical study of preference-based spatial co-location pattern mining.Offers solutions to various challenges and issues in preference-based spatial co-location pattern minin | | 叢書名稱 | Big Data Management | | 圖書封面 |  | | 描述 | The development of information technology has made it possible to collect large amounts of spatial data on a daily basis. It is of enormous significance when it comes to discovering implicit, non-trivial and potentially valuable information from this spatial data. Spatial co-location patterns reveal the distribution rules of spatial features, which can be valuable for application users. This book provides commercial software developers with proven and effective algorithms for detecting and filtering these implicit patterns, and includes easily implemented pseudocode for all the algorithms. Furthermore, it offers a basis for further research in this promising field..Preference-based co-location pattern mining refers to mining constrained or condensed co-location patterns instead of mining all prevalent co-location patterns. Based on the authors’ recent research, the book highlights techniques for solving a range of problems in this context, including maximal co-location pattern mining, closed co-location pattern mining, top-k co-location pattern mining, non-redundant co-location pattern mining, dominant co-location pattern mining, high utility co-location pattern mining, user-prefer | | 出版日期 | Book 2022 | | 關(guān)鍵詞 | Condensed representation; Optimization; Preference; Spatial co-location pattern; Spatial data mining | | 版次 | 1 | | doi | https://doi.org/10.1007/978-981-16-7566-9 | | isbn_softcover | 978-981-16-7568-3 | | isbn_ebook | 978-981-16-7566-9Series ISSN 2522-0179 Series E-ISSN 2522-0187 | | issn_series | 2522-0179 | | copyright | China Science Publishing & Media Ltd (Science Press) 2022 |
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