Unknown　word　recognition　is　one　of　the　important　research　contents　of　natural　language　processing.　However,　there　are　still　problems　such　as　sparse　data,　corpus　noise,　and　various　forms　of　expressions　for　the　identification　of　micro-blog　short　words.　This　paper　proposes　an　unknown　words　recognition　method　POS-FP　(Frequent　Pattern　growth　with　part-　of-speech)for　micro-blog　short　text.　Firstly,　the　candidate　unknown　words　are　obtained　by　combing　the　N-grams　model　and　frequent　item　sets.　Then　the　unknown　word　is　filtered　and　verified　by　the　improved　mutual　information,　information　entropy　and　context　dependence.　Finally,　the　open　verification　method　is　used　to　obtain　final　unknown　word.　Experiments　show　that　the　algorithm　improved　the　unknown　word　recognition　for　micro-blog　short　texts.　©　2018　IEEE.