Homeopathy decision is a decision under uncertainty and an essential activity for accurate treatment. Expert systems have long history of application in medical diagnosis. In this paper we study application of Fuzzy Expert System and decision tree for selection of suitable remedy in Homeopathy. A decision made by Homeopath is highly dependent on the quality of selected rubrics. The rubrics are collected during case taking and generally contains expressions that might be considered fuzzy, such as 'never', 'sometimes', 'always', and so on, making it difficult to model them with conventional computational methods. In this context, fuzzy set theory in expert systems is an interesting tool to deal with the representation of inaccurate medical entities. Hence, we can go from natural language (linguistic variables) to numerical variables which are more convenient to handle in a computer. The proposed method reduces sensitivity of system to homeopath mistakes and increase security of system.
Abstract-The growing of Web 2.0 has led to huge information is available. The analysis of this information can be very useful in various fields. In this regards, opinion mining and sentiment analysis are one of the most interesting task that many researchers have paid attention for two last decades. However, this task involves to some challenges that a very important challenge is the different polarity of words in various domain and context. Word polarity is an important feature in the determination of review polarity through sentiment analysis. Existing studies have proposed n-gram technique as a solution which allows the matching of the selected words to the lexicon. However, identification of word polarity using the standard ngram method poses limitation as it ignores the word placement and its effect according to the contextual domain. Therefore, this study proposes a linguistic-based model to extract the word adjacency patterns to determine the review polarity. The results reflect the superiority of the proposed model compared to other benchmarking approaches.
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