With　the　rapid　development　of　big　data　technology,　electronic　documents　are　more　and　more　widely　used.　Aiming　at　the　characteristics　of　large　amount　of　data,　complex　format　and　non-standard　information　data　of　electronic　documents,　this　paper　uses　data　mining　technology　to　realize　the　correlation　construction　between　documents.　Firstly,　on　the　basis　of　dynamic　incremental　association　rules,　according　to　the　characteristics　of　electronic　document　business,　the　association　rules　are　improved.　Secondly,　the　advantages　of　Boolean　matrix　operation,　original　data　association　rules　and　frequent　2-item　set　are　used　to　improve　the　acquisition　ability　of　the　system　for　frequent　items　of　document　features.　The　experimental　results　show:　that　algorithm　in　this　paper　has　higher　computational　efficiency　in　the　process　of　file　increment　change　and　deletion　change,　and　is　suitable　for　electronic　file　processing　in　the　case　of　big　data.　©　The　Author(s),　under　exclusive　licence　to　Springer　Science+Business　Media,　LLC,　part　of　Springer　Nature　2024.