图 书 馆
语义信息检索的三部分神经文档语言模型A Tri-Partite Neural Document Language Model for Semantic Information Retrieval |
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| 课程网址: | http://videolectures.net/eswc2018_nguyen_information_retrieval/ |
| 主讲教师: | Gia Hung Nguyen |
| 开课单位: | 图卢兹大学 |
| 开课时间: | 2018-07-10 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Previous work in information retrieval have shown that using evidence, such as concepts and relations, from external knowledge resources could enhance the retrieval performance. Recently, deep neural approaches have emerged as state-of-the art models for capturing word semantics that can also be efficiently injected in IR models. This paper presents a new tri-partite neural document language framework that leverages explicit knowledge to jointly constrain word, concept, and document learning representations to tackle a number of issues including polysemy and granularity mismatch. We show the effectiveness of the framework in various IR tasks including document similarity, document re-ranking, and query expansion. |
| 关 键 词: | 信息检索; 深度神经; 文档学习 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2022-12-20：chenjy |
| 最后编审: | 2023-05-11：chenjy |
| 阅读次数: | 13 |