基于设计模式的意见挖掘系统框架

Nien-Lin Hsueh
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引用次数: 3

摘要

由于大量的意见丰富的网络资源,如论坛,评论网站,博客和新闻语料库的数字形式,目前的许多研究都集中在情感分析领域。人们打算开发一种系统,可以识别和分类电子文本中所代表的意见或情绪。一种准确的预测情绪的方法可以使我们能够从互联网上提取意见,并预测在线客户的偏好,这对经济或营销研究来说是有价值的。本文提出了一种观点挖掘框架,即FOM (framework of opinion mining),用于在热门网站中收集非结构化文章,并以半自动的方式分析观点和情感。该框架采用面向对象的设计模式开发,以支持灵活性和可维护性等。利用FOM框架,可以方便地替换和集成新的分析算法。本文将演示一个基于facebook文本的台湾洪水预测应用程序。
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A Framework for Opinion Mining System with Design Pattern
Due to the sheer volume of opinion rich web resources such as discussion forum, review sites, blogs, and news corpora available in digital form, much of the current research is focusing on the area of sentiment analysis. People are intended to develop a system that can identify and classify opinion or sentiment as represented in an electronic text. An accurate method for predicting sentiments could enable us, to extract opinions from the internet and predict on-line customer's preferences, which could prove valuable for economic or marketing research. In this paper we present a framework for opinion mining in Traditional Chinese-called FOM (Framework of Opinion Mining) to collect unstructured articles in the popular web site and analyse the opinion and sentiment in the semi-automatic way. The framework is developed by objected oriented design patterns, such as to support the flexibility and maintainability. With the FOM framework, new analysis algorithm can be easily replaced and integrated in a new application. A flood predication application based on facebook text in Taiwan will be demonstrated in this paper.
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