| 书目名称 | Knowledge Discovery from Multi-Sourced Data | | 编辑 | Chen Ye,Hongzhi Wang,Guojun Dai | | 视频video | | | 概述 | Provides various techniques to discover useful knowledge based on different data models of multi-sourced data.Covers both truth discovery and fact discovery based on different data quality properties | | 丛书名称 | SpringerBriefs in Computer Science | | 图书封面 |  | | 描述 | This book addresses several knowledge discovery problems on multi-sourced data where the theories, techniques, and methods in data cleaning, data mining, and natural language processing are synthetically used. This book mainly focuses on three data models: the multi-sourced isomorphic data, the multi-sourced heterogeneous data, and the text data. On the basis of three data models, this book studies the knowledge discovery problems including truth discovery and fact discovery on multi-sourced data from four important properties: relevance, inconsistency, sparseness, and heterogeneity, which is useful for specialists as well as graduate students.. .Data, even describing the same object or event, can come from a variety of sources such as crowd workers and social media users. However, noisy pieces of data or information are unavoidable. Facing the daunting scale of data, it is unrealistic to expect humans to “label” or tell which data source is more reliable.Hence, it is crucial to identify trustworthy information from multiple noisy information sources, referring to the task of knowledge discovery.. .At present, the knowledge discovery research for multi-sourced data mainly faces two | | 出版日期 | Book 2022 | | 关键词 | Truth Discovery; Source Reliability; Integrity Constraints; Optimization Framework; Fact Extraction; Data | | 版次 | 1 | | doi | https://doi.org/10.1007/978-981-19-1879-7 | | isbn_softcover | 978-981-19-1878-0 | | isbn_ebook | 978-981-19-1879-7Series ISSN 2191-5768 Series E-ISSN 2191-5776 | | issn_series | 2191-5768 | | copyright | The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 |
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发表于 2025-3-21 18:42:38
