| 書目名稱 | Linguistic Structure Prediction |
| 編輯 | Noah A. Smith |
| 視頻video | http://file.papertrans.cn/587/586702/586702.mp4 |
| 叢書名稱 | Synthesis Lectures on Human Language Technologies |
| 圖書封面 |  |
| 描述 | A major part of natural language processing now depends on the use of text data to build linguistic analyzers. We consider statistical, computational approaches to modeling linguistic structure. We seek to unify across many approaches and many kinds of linguistic structures. Assuming a basic understanding of natural language processing and/or machine learning, we seek to bridge the gap between the two fields. Approaches to decoding (i.e., carrying out linguistic structure prediction) and supervised and unsupervised learning of models that predict discrete structures as outputs are the focus. We also survey natural language processing problems to which these methods are being applied, and we address related topics in probabilistic inference, optimization, and experimental methodology. Table of Contents: Representations and Linguistic Data / Decoding: Making Predictions / Learning Structure from Annotated Data / Learning Structure from Incomplete Data / Beyond Decoding: Inference |
| 出版日期 | Book 2011 |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-031-02143-5 |
| isbn_softcover | 978-3-031-01015-6 |
| isbn_ebook | 978-3-031-02143-5Series ISSN 1947-4040 Series E-ISSN 1947-4059 |
| issn_series | 1947-4040 |
| copyright | Springer Nature Switzerland AG 2011 |
|Archiver|手機(jī)版|小黑屋|
派博傳思國際
( 京公網(wǎng)安備110108008328)
GMT+8, 2025-10-6 10:23
發(fā)表于 2025-3-21 16:14:22
