With　the　rapid　growth　of　microblog　data,　extracting　hot　topics　from　vast　amounts　of　microblog　posts　has　become　a　research　hotspot.　The　traditional　methods　for　hot　term　extraction　can　hardly　apply　to　microblog　data,　thus　a　life　value　calculation　model　based　on　aging　theory　is　established　to　extract　hot　terms.　Then,　a　hot　term　co-occurrence　network　is　built　based　on　the　correlations　between　hot　terms.　Aiming　at　the　problem　that　traditional　clustering　methods　can　hardly　handle　the　hot　term　overlap　between　different　topics　and　can　not　deal　with　vast　amounts　of　data　efficiently,　a　term　clustering　method　based　on　multi-label　propagation　algorithm　(TCMLPA),　which　has　a　nearly　linear　time　complexity,　is　proposed　to　detect　hot　topics　in　hot　term　co-occurrence　network.The　experimental　results　show　that　life　value　calculation　model　can　filter　noise　and　extract　hot　terms　effectively.　Meanwhile,　TCMLPA　ensures　the　stability　of　clustering　result　and　improves　the　accuracy　and　efficiency　of　hot　topic　detection.　©,　2015,　Journal　of　Pattern　Recognition　and　Artificial　Intelligence.　All　right　reserved.