The mining and analysis of smart traffic card data can provide strong support for urban traffic construction and urban management. However, most of the existing research data only include data about bus or subway, and mainly focus on macro-travel patterns. In view of this problem, taking a city traffic card data as the example, which contains the multi-source daily travel data of urban residents including bus, subway and taxi, the concept of tour chain was put forward to model the behavior of residents. On this basis, the periodic travel characteristics of different dimensions were given. Then a spatial periodic feature extraction method based on the longest common subsequence was proposed, and the travel rules of urban residents were analyzed by clustering analysis. Finally, the effectiveness of this method was verified by five evaluation indexes defined by the rules, and the clustering result was improved by 6.8% by applying the spatial periodic feature extraction method, which is helpful to discover the behavior pattern of residents.

This thesis focused on the traditional and message-based SoftMan's communication approach which has some problems in the aspects of expression ability, communication efficiency and quality. Based on the early research in SoftMan system and its communication theory, as well as SoftMan cogmatics model and context awareness mechanism, this thesis proposed the Context driven SoftMan Knowledge Communication (CSMKC) framework by learning from mature Agent communication language specification. First, the message layer, the knowledge layer and the scenarios layer in knowledge communication framework were designed; second, from the three aspects of implementation of message layer, knowledge layer and scenarios layer, the key points of knowledge communication achievements of scenario-driven SoftMan were introduced; finally, different SoftMan's communication in knowledge grade and the maintenance of scenario context were realized basically. The experimental results show that when the later content has high dependence on communication scenario, compared with the traditional message-based SoftMan communication approach, the communication overhead per unit time of CSMKC reduces by 46.15% averagely. Thus, the higher dependence on the scene, the more obvious CSMKC advantages in terms of reducing communication while accomplishing a task in the system.