Nursing-care text classification using additional term information from Web.
Grad. Sch. of Eng., Univ. of Hyogo, Himeji, JapanDOI: 10.1109/FUZZY.2011.6007540 Conference: FUZZ-IEEE 2011, IEEE International Conference on Fuzzy Systems, Taipei, Taiwan, 27-30 June, 2011, Proceedings
In this paper, for improving performance of the nursing-care text classification, we introduce a mechanism of retrieving terms from Web. Every year, the nursing-care texts are collected by using Web application to improve nursing-care quality in Japan. The collected nursing-care texts are decomposed into morphemes (i.e., terms), and then terms are stored as a term list. Each text is represented as a feature vector by using the term list and classified using a SVM based classification system. The training data sets for constructing SVM based classification system are different from the evaluation data sets. That is, there are differences between the term lists of the nursing-care texts because the nursing-care texts are collected and evaluated every year. To cover this difference, we introduce a mechanism of retrieving terms from Web. A new term which appeared in the evaluation data sets is used as a query of a search engine. The terms in the term list are also used as queries. Terms are represented by the search results, and then are compared with each other. We use the most similar term in the term list as an alternative of the new term. From experimental results, we show effectiveness of our proposed method.
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ABSTRACT: In order to improve the nursing-care quality, a"Web based Nursing-care Quality Improvement System" have been proposed and operating continuously. In the proposed system, for evaluating actual nursing-care process, freestyle Japanese texts which are called "nursing-care texts" are collected through the Internet in Japan. The nursing-care experts can evaluate actual nursing-care process and recommend some improvements to nurses by reading the collected nursing-care texts carefully. Since the number of nursing-care experts who can evaluate the nursing-care texts is a few, it is hard to do the above mentioned evaluation process for a large number of nurses. To assist nursing-care experts in evaluating the nursing-care texts, a computer aided nursing-care text classification system has been developed. In this paper, we propose a method to improve the classification performance of the computer aided nursing-care text classification system. Dependency relation between terms is extracted from the nursing-care text and used the dependency as a feature value which represents characteristics of the nursing-care text.Emerging Trends in Engineering and Technology (ICETET), 2012 Fifth International Conference on; 11/2012
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ABSTRACT: Since Japan is one of the most aging countries, it is very important for us to improve the nursing-care quality. For improving the nursing-care quality, a Web-based nursing-care quality improvement system have been proposed and operating experimentally and continuously. A kind of collected data by the Web-based system is freestyle Japanese text called "nursing-care texts". The nursing-care texts are used for evaluating actual nursing-care process. In order to assist nursing-care experts in evaluating the nursing-care texts, a computer aided nursing-care text classification system has been developed. In this paper, we propose a phrase based feature vector definition for classifying the nursing-care texts. The dependency relation based feature vector definition has been proposed in our previous work. As another feature vector definition method, we propose a phrase based feature vector definition method. Phrases are found by using the dependency relation analysis and stored into a phrase list. We also define a similarity between phrases because each phrase consists of some kinds of words. From experimental results, we show that our phrase based feature vector contributes the classification performance.Proceedings of the 2013 IEEE International Conference on Systems, Man, and Cybernetics; 10/2013
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