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测量会话的语义连贯性

Measuring Semantic Coherence of a Conversation
课程网址: http://videolectures.net/iswc2018_vakulenko_measuring_coherence_c...  
主讲教师: Svitlana Vakulenko
开课单位: 维也纳经济与商业大学信息商业研究所
开课时间: 2018-11-22
课程语种: 英语
中文简介:
作为人类与计算机交互的一种方式,对话系统已经变得越来越流行。为了能够提供智能响应,会话系统必须正确地建模会话的结构和语义。在本文中,我们介绍了测量会话中与背景知识相关的语义连贯性的任务,该任务依赖于识别会话中引入的概念之间的语义关系。我们提出并评估了基于图和机器学习的方法,以使用知识图、它们的向量空间嵌入和单词嵌入模型作为背景知识的来源来测量语义一致性。我们在评估结果中展示了这些方法如何能够在Ubuntu对话语料库上发现对话中的不同连贯模式。
课程简介: Conversational systems have become increasingly popular as a way for humans to interact with computers. To be able to provide intelligent responses, conversational systems must correctly model the structure and semantics of a conversation. In this paper, we introduce the task of measuring semantic (in)coherence in a conversation with respect to the background knowledge, which relies on identification of semantic relations between concepts introduced during a conversation. We propose and evaluate graph-based and machine learning approaches for measuring semantic coherence using knowledge graphs, their vector space embeddings and word embedding models, as sources of background knowledge. We demonstrate in our evaluation results how these approaches are able to uncover different coherence patterns in conversations on the Ubuntu Dialogue Corpus.
关 键 词: 人类与计算机交互; 语义连贯性任务; 测量语义一致性; Ubuntu对话语料库
课程来源: 视频讲座网
数据采集: 2023-01-06:cyh
最后编审: 2023-01-07:cyh
阅读次数: 32