面向情感分析的英语歧义消解

Kamalakshi V. Deshmukh, S. Shiravale
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引用次数: 1

摘要

今天的市民需要一个平台来登记他们对市政公司的投诉。市民需要向市政公司提交他们的日常投诉。在像电话这样的传统系统中,投诉的登记是一种非常耗时的方法。客户必须等待,直到客服人员接到电话。该系统是为浦那市政公司(PMC)设计的,市民可以在其中插入查询,并通过短文本理解和机器学习算法向市民提供智能回复。在帖子查询系统中,通过情感分析对公民的情感进行分析。因此,根据公民投诉的强度对特定公民进行优先处理。理解短文本是系统的主要挑战,如短文本不遵循书面语言的语法,短文本没有足够的统计数据来支持文本挖掘等方法,短文本含糊不清且有噪声。在该系统中,理解自然语言的语义知识由知识库提供。该系统将帮助许多组织以更少的人力来确保提供优质的服务和客户满意度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ambiguity Resolution in English Language for Sentiment Analysis
Today’s citizens need a platform where they can register their complaints about municipal corporation. Citizens need to submit their daily complaints for municipal corporation. In a traditional system like Telephonic system for registration of complaints is a very time-consuming method. The customer has to wait until call is received by service executive. The proposed system is for the Pune Municipal Corporation (PMC) where citizens can insert query and intelligent reply is given to the citizen by short text understanding and machine learning algorithms. In the post query system analyses the sentiment of citizen by sentiment analysis. Accordingly, priorities to the given citizens on the basis of the intensity of the citizen complaint. Understanding the short text is the major challenge in the system like short texts do not follow the syntax of written language, short text does not have sufficient statistics to support for approaches like text mining, short text is ambiguous and noisy. In this system to understand natural language semantic knowledge is provided by the knowledgebase. This system will help many organizations to ensure quality service provision and customer satisfaction with less human efforts.
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