Recently, life-logging service which has expanded to measure and record the daily life of the users and to share with others are increasing. In particular, as life-logging services based on the application has become popular with the development of wearable-devices and smart-phones, the contents of this service are produced by user behavior and are provided in infographic menu form. The purpose of this paper is to extract user behavior and classify for making contents items of life-logging service. For this paper, the first of all, we discuss the definition and characteristics of life-logging and research the contents based on user behavior related to life-logging by the publications including thesis, articles, and books. Secondly, we extract and classify the user behavior to build the contents for life-logging service. We gather users' action words from publication materials, researches, and contents of existing life-logging service. And then collected words are analyzed by FGI (Focus Group Interview) and survey. As the result, 39 words which suit for contents of life-logging service are extracted by verify suitability. Finally, the extracted 39 words are classified for 19 categories -'Eat', 'Keep house', 'Diet', 'Travel', 'Work out', 'Transit', 'Shoot', 'Meet', 'Feel', 'Talk', 'Care for', 'Drive', 'Listen', 'Go online', 'Sleep', 'Go', 'Work', 'Learn', 'Watch' - which are suggested by the surveys, statistical analysis, and FGI. We will discuss the role and limitations of this results to build contents configuration based on life-logging application in this study.