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Improving Trust in Automation of Social Promotion

机译:改善对社会促进自动化的信任

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摘要

We build a conversational agent performing social promotion (CASP) to assist in automation of interacting with friends and managing other social network contacts. This agent employs a domain-independent natural language relevance technique which filters web mining results to support a conversation with friends and other network members. This technique relies on learning parse trees and parse thickets (sets of parse trees) of paragraphs of text such as Facebook postings. We evaluate the robust intelligent features and trust in behavior of this conversational agent in the real world. It is confirmed that maintaining a relevance of automated posting is essential in retaining trust and efficient social promotion of CASP.
机译:我们建立一个执行社会促销(CASP)的会话代理,以协助与朋友互动的自动化,并管理其他社交网络联系人。该代理采用域独立的自然语言相关技术,其过滤网站挖掘结果,以支持与朋友和其他网络成员的对话。这种技术依赖于学习解析树木和解析丛生的文本段落(如诸如Facebook帖子的文本段落)。我们评估真正的智能特征和对现实世界中这种会话代理的行为的信任。据证实,维持自动化岗位的相关性对于保留信任和有效的CASP的社会促进至关重要。

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