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从网上提取公开信息Open Information Extraction from the Web |
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| 课程网址: | http://videolectures.net/akbcwekex2012_etzioni_information_extrac... |
| 主讲教师: | Oren Etzioni |
| 开课单位: | 艾伦人工智能研究所 |
| 开课时间: | 2012-07-13 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Traditionally, Information Extraction (IE) has focused on satisfying precise, narrow, pre-specified requests from small homogeneous corpora (e.g., extract the location and time of seminars from a set of announcements). Shifting to a new domain requires the user to name the target relations and to manually create new extraction rules or hand-tag new training examples. This manual labor scales linearly with the number of target relations. This paper introduces Open IE (OIE), a new extraction paradigm where the system makes a single data-driven pass over its corpus and extracts a large set of relational tupleswithout requiring any human input. The paper also introduces TEXTRUNNER, a fully implemented, highly scalable OIE system where the tuples are assigned a probability and indexed to support efficient extraction and exploration via user queries. We report on experiments over a 9,000,000 Web page corpus that compare TEXTRUNNER with KNOWITALL, a state-of-the-art Web IE system. TEXTRUNNER achieves an error reduction of 33% on a comparable set of extractions. Furthermore, in the amount of time it takes KNOWITALL to perform extraction for a handful of pre-specified relations, TEXTRUNNER extracts a far broader set of facts reflecting orders of magnitude more relations, discovered on the fly. We report statistics on TEXTRUNNER’s 11,000,000 highest probability tuples, and show that they contain over 1,000,000 concrete facts and over 6,500,000more abstract assertions. |
| 关 键 词: | 网络; 公开信息 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-08：heyf |
| 阅读次数: | 29 |