A TOM (topic occurrence-oriented merging) algorithm is presented to solve topic maps merging problem in distributed circumstance. The contents of topic and occurrence are selected by TOM as the research objects. Through judging topic name similarity and occurrence data/resource similarity, the conclusion is drawn that whether two topics can be merged. The experimental source data are taken from IEEE and EI. Through evaluating the periodicals published by IEEE in 2004 which contents are “knowledge”-related and can be searchable by EI; the quality of TOM is examined according to the criterions of recall ratio, precision ratio and the compound of them. Finally it is proved that TOM is a kind of precise merging algorithm for distributed topic maps.

Please note: This publication is in Chinese!