Open　domain　question　answering　(QA)　represents　a　challenge　of　natural　language　processing,　aiming　at　returning　exact　answers　in　response　to　natural　language　questions.　A　novel　pattern　learning　method　for　QA　is　developed.　The　key　idea　is　to　get　answers　using　answer　patterns　learned　from　the　Web.　Although　many　other　QA　systems　use　the　pattern　based　method,　the　method　in　this　paper　is　implemented　automatically　and　it　can　handle　the　problems　other　systems　fail,　such　as　the　weakness　of　pattern　restriction　and　so　on.　The　experiment　result　on　the　TREC　data　indicates　that　the　method　is　effective.　It　solves　not　only　the　questions　relying　on　simple　patterns,　but　also　the　questions　that　need　complex　patterns　for　answer　extraction.　The　question　number　of　the　latter　is　about　80%　in　the　question　set　of　the　TREC.