With the coming of knowledge management era, academic institutions also begin to engage in knowledge management (KM) activities, hoping that researchers can understand the relationship between research topics. However, most of the KM activities focusing on academic papers need research¡¦s effort to code and classify paper¡¦s content, and there is still no measurement of relationship between research topics from prior researches. Therefore, this thesis will propose a methodology to measure the relationship between research topics and grab the data of National Central Library from internet to construct a knowledge relationship system. This system will analyze both dissertation¡¦s and thesis¡¦ content, such as keywords, abstracts, etc., and calculate two measurements that are relation strength and relation similarity to assess the direct and indirect relationship between two research topics. Moreover, this thesis found a phenomenon that there is high diversity of Chinese keyword¡¦s usage and the Chinese translation of English keyword. To overcome this incident, the database for Chinese keywords is built. This database will excerpt the mapping of Chinese keywords usage and its translation from the abstract of thesis. Finally, the trend of research topics in information-related domain using different aspects, such as different years, different schools and different departments are analyzed. The result of analysis includes: