In this study, we propose a novel concept of intelligent topic map, which embodies the multi-level, multi-granularity and inherent relevant characteristics of knowledge and realizes knowledge reasoning. With the intelligent topic map as infrastructure, we design a specific ontology fusion process for multi-resource knowledge fusion. Also, we define the taxonomy of merging conflicts which occur during the process of intelligent topic maps merging. We define and classify merging conflicts into data-level conflicts, structure-level conflicts, rule-level conflicts and temporary-level conflicts. We propose the detection and resolution schemes for each merging conflict. Additionally, we implement the multi-resource knowledge fusion conflicts detection and resolution system based on rules. The experimental results show that our method can correctly detect and resolve the conflicts in topic maps merging and it is helpful to improve the quality of multi-resource knowledge fusion.