A fuzzy information retrieval for respiratory diseases

Weenawadee Muangon
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引用次数: 1

Abstract

Respiratory diseases can be found in many countries, particular in a tropical climate country such as Thailand. Generally, the respiratory disease associated with breathing system which is several organs involved such as nose, throat, larynx, bronchial lung etc. The symptoms are consistent with organs; moreover, the nature of the symptoms is very similar. Therefore, inexperienced peoples are difficult to diagnose the symptoms correctly. In this paper, we present an information retrieval system based on the concept of fuzzy logic to be considered vagueness information and uncertainly on text document. The fuzzy logic model applied in a simple way to comprehensive query form to help input uncertainly of users. The diseased content represented as a vector space model; furthermore, cosine similarity technique is used to rank the retrieved results. To experiment, we provide an IR system that work on mentioned model. Moreover, we get query from three type's users that are general peoples, patients and doctors. The results show the average precision around 67 percent, recall 70 percent and F-measure about 70 percent.
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呼吸系统疾病的模糊信息检索
许多国家都有呼吸道疾病,特别是在泰国这样的热带气候国家。一般来说,呼吸系统疾病与呼吸系统有关,呼吸系统涉及几个器官,如鼻子、喉咙、喉头、支气管肺等。症状与器官一致;而且,症状的性质非常相似。因此,没有经验的人很难正确诊断症状。本文提出了一种基于模糊逻辑概念的信息检索系统,以考虑文本文档的模糊性信息和不确定性。将模糊逻辑模型以简单的方式应用于综合查询表单,帮助用户输入不确定性。病态内容用向量空间模型表示;此外,使用余弦相似度技术对检索结果进行排序。为了进行实验,我们提供了一个在上述模型上工作的红外系统。此外,我们得到了三类用户的查询:一般人、病人和医生。结果显示,平均精度约为67%,召回率为70%,F-measure约为70%。
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