A directed graph based feature definition for classifying nursing-care texts

• Published in: 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC) pp. 3691 - 3695
• Main Authors: Nii, Manabu, Takahama, Kazunobu, Uchinuno, Atsuko, Sakashita, Reiko
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.10.2014
• Subjects: Feature extraction; Indexes; Medical services; Support vector machine classification; Training data; Vectors
• ISSN: 1062-922X; 2577-1655
• DOI: 10.1109/SMC.2014.6974504

In the aging society such as Japan, we feel large importance for improving the quality of nursing-care to keep our quality of life. Development of a computer aided evaluation system for improving the quality of nursing-care is our final goal. In order to evaluate the quality of actual nursing in wide areas in Japan, we have been collecting texts that are written by nurses using our Web based system. A SVM based classification system has been developed to classify such nursing-care texts, and a dependency relation based feature vector definition has also been proposed in our previous researches. When we train the SVM based classification system, pre-classified nursing-care texts by a few nursing-care experts are used as a training data set. Some texts in the training data are similar but classified into different classes. To classify the nursing-care texts with high accuracy, we need to extract numerical features that can express characteristics of the original text. In this paper, we explain some feature vector definitions and propose a directed graph based feature vector definition.