|| In this study, cluster analysis was used to classify the data sets in relation to the species composition of catches. Based on the results of cluster analysis, data sets were grouped into nine clusters and assigned to specific fishing types. The CPUE standardization was conducted by generalized linear model (GLM). The effect of cluster was the most effective variable for explaining the variance of nominal CPUE. Generally, the trends of standardized CPUE obtained from GLMs with cluster effect were relatively smoother than those obtained from GLMs without cluster effect. Therefore, we would suggest that the standardized CPUE series obtained from GLM with cluster effect based on all data sets might be more appropriate to be applied to stock assessment as relative abundance indices. This study evaluated the stock status of swordfish in the Indian Ocean based on the sex-specific age-structured integrated approach (ASIA). The results of most scenarios indicated that the current fishing intensity was lower than MSY level and the current spawning biomass was higher than MSY level, while the current fishing intensity may slightly higher than MSY level when a lower reproductivity was assumed for swordfish. For southwest Indian Ocean, the results of all scenarios indicated that the status of swordfish in the Indian Ocean and in the southwestern Indian Ocean might not be overfishing or overfished. However, the stock status would be more pessimistic when the assumption of lower reproductivity was adopted. This study conducted the CPUE standardization for southern bluefin tuna caught by Taiwanese longline fishery using GLM. Standardized CPUEs generally reveal quite different trends for different area. Generally, standardized CPUEs substantially decreased for all areas in recent years. It is apparent that the CCSBT statistical areas may not be appropriate for Taiwanese SBT fishery. In addition, the CPUEs of other tunas may not be explanatory effects when conducting CPUE standardization for Taiwanese SBT fishery.