After　document　and　image　retrieval,　shape　retrieval　is　seen　as　the　next　step　in　the　search　process.　Numerous　techniques　have　been　proposed　to　retrieve　shapes　meta-data　considering　shapes　similarity　but　these　techniques　normally　suffer　from　non-interactive　running　times.　A　widely　used　approach,　which　has　its　origins　in　document　retrieval,　and　is　successfully　been　applied　for　image　retrieval,　is　based　on　＂bag-of-words＂.　Methods　using　this　approach　have　the　potential　to　support　fast,　real　time　retrieval　of　shapes　over　the　large　databases.　This　research　examines　these　approaches　and　summarizes　the　techniques　used　to　convert　shapes　to　their　＂bag　of　words＂　representations.　This　research　also　explores　the　mechanism　these　techniques　adopts　to　facilitate　and　enhance　interactive　search　times.