It is of great significance for researchers to master the development of research field through the analysis of published papers. In order to meet this requirement, a visual analysis method based on extended B_cp index was proposed. First of all, keywords containing phrases are automatically extracted from the title, abstract, and author provided keywords. Then co-occurrence relationship between these keywords was extracted. According to these keywords, LDA algorithm was used to extract topics. Then, an extended B_cp index was proposed to measure the development state of keywords. Based on this method, a visual analytic tool VISExplorer was designed and implemented. VISExplorer can show the distribution and development trend of domain topics, recommend high-quality papers, and browse top authors. Finally, taking the domain of visualization as an example, VISExplorer was conducted in real cases of publications on IEEE VIS Conference from 1990 to 2018, and the usefulness and effectiveness are proved by user’s feedbacks.