Transaction　data　contain　a　large　amount　of　information　of　individuals　and　entities.　Publication　of　these　data　can　provide　important　resources　for　researching　such　as　association　rule　mining,　recommendation　systems　and　user　behavior　prediction　ect.　But　on　the　other　hand,　it　will　compromise　individual　privacy.　Recently,　many　works　focus　on　privacy　preserving　transaction　data　publishing,　especially　on　anonymous　publishing.　In　this　paper,　we　will　systematically　summarize　and　evaluate　different　anonymous　approaches　for　transactional　data　publication.　©　2012　IEEE.