The most of conventional information services are based on the implicit premise that the users has already defined their desired information. This study proposes a mobile information service that allows the users who have not yet defined their desired information or whose desired information varies according to the situation to get appropriate information. When the user can specify their desired information to the system explicitly, the authors develop a "Pull" service. Conversely, when the user cannot verbally specify their desired information to the system, this study provides "Push" service and "Don't disturb" option for the user who does not welcome this service. This study considers the characteristics of the environment of mobile terminal to focus on "Time", "Place" and user's "Preference": long term and short term preference. This study also creates rules, algorithms and filtering to the service. Furthermore, the results of experiments have been discussed to verify the idea that different of user desired requires different information services.

Nowadays more people have started using their mobile phone to access information they need from anywhere at anytime. In advanced mobile technology, Location Service allows users to quickly pinpoint their location as well as makes a recommendation to fascinating events. However, users desire more appropriate recommendation services. In other words, the message service should push a message at a proper place in time. In consequence, customers obtain a higher level of satisfaction. In this paper, we propose a framework of time, place, purpose and personal profile based recommendation service. We illustrate scenarios in "push", "pull" and "don't disturb" services, where our DB queries can recommend the relevant message to users. The three factors: time, place and purpose are mutually dependent and the basic rules to analyze the essential data are summarized. We also create algorithms for DB query. We are filtering messages by one important factor: personal profile such as user's preference and degree of preference. Furthermore, we discuss an implementation of the prototype system, including results of experimental evaluation.