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.

The case postpositions usually have more than one semantic role in Korean. The adverbial postpositions among various postpositions especially make the development of Korean-based machine translation system difficult, because they have more semantic roles than others. In this paper, we describe a new method for resolving semantic ambiguities of adverbial postpositions using decision tree induction. The lack of training examples in decision tree induction is overcome by clustering words into classes using a kind of greedy algorithm. The cross validation results show that the presented method achieves 76.5% of accuracy on the average, which is 20.3% improvement over the baseline method.