| 書目名稱 | Mining Structures of Factual Knowledge from Text | | 副標(biāo)題 | An Effort-Light Appr | | 編輯 | Xiang Ren,Jiawei Han | | 視頻video | http://file.papertrans.cn/635/634670/634670.mp4 | | 叢書名稱 | Synthesis Lectures on Data Mining and Knowledge Discovery | | 圖書封面 |  | | 描述 | The real-world data, though massive, is largely unstructured, in the form of natural-language text. It is challenging but highly desirable to mine structures from massive text data, without extensive human annotation and labeling. In this book, we investigate the principles and methodologies of mining structures of factual knowledge (e.g., entities and their relationships) from massive, unstructured text corpora. Departing from many existing structure extraction methods that have heavy reliance on human annotated data for model training, our effort-light approach leverages human-curated facts stored in external knowledge bases as distant supervision and exploits rich data redundancy in large text corpora for context understanding. This effort-light mining approach leads to a series of new principles and powerful methodologies for structuring text corpora, including (1) entity recognition, typing and synonym discovery, (2) entity relation extraction, and (3) open-domain attribute-valuemining and information extraction. This book introduces this new research frontier and points out some promising research directions. | | 出版日期 | Book 2018 | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-01912-8 | | isbn_softcover | 978-3-031-00784-2 | | isbn_ebook | 978-3-031-01912-8Series ISSN 2151-0067 Series E-ISSN 2151-0075 | | issn_series | 2151-0067 | | copyright | Springer Nature Switzerland AG 2018 |
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