图 书 馆
回指和共指解析：仍然是一个难题？它已经走了多远，对NLP有什么影响，前进的道路是什么？Anaphora and coreference resolution: still a hard nut to crack? How far has it gone, what is its impact on NLP and what are the ways forward? |
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| 课程网址: | https://videolectures.net/jota_mitkov_anaphora/ |
| 主讲教师: | Ruslan Mitkov |
| 开课单位: | JOTA会议 |
| 开课时间: | 2018-05-08 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Anaphora and coreference resolution are arguably among the most challenging Natural Language Processing (NLP) tasks. Research in anaphora resolution and coreference resolution has focused almost exclusively on the development and intrinsic evaluation of various algorithms. While publications report positive results, the speaker shows that the replication of some of the best-known algorithms reveals reasons for concern in that the performance is far from ideal and the evaluation is far from transparent. Anaphora and coreference resolution as tasks are crucial for the operation of NLP systems and should not be regarded in isolation but only in the wider picture of NLP applications. The extrinsic evaluation or the impact of an anaphora or coreference resolution module on a larger NLP system of which they are part, is an under-researched topic and several studies conducted by the speaker, seek to fill in this gap. More specifically, the speaker discusses whether anaphora and coreference resolution can improve (and if they can, to what extent?) or not the performance of four NLP applications: text summarisation, term extraction, text categorisation and textual entailment. The presentation finishes with suggested ways forward as to how anaphora and coreference resolution can do better and outlines the latest related research of the author. |
| 关 键 词: | 回指解析; 共指指解; NLP |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2024-04-18：liyq |
| 最后编审: | 2024-05-31：liyy |
| 阅读次数: | 27 |