Pop-ups　are　a　recently　popular　way　of　human-computer　interaction,　allowing　viewers　to　actively　participate　in　the　discussion　of　a　film　video,　but　pop-ups　can　be　deleted　due　to　exceeding　the　size　limit　of　the　pop-up　pool,　and　pop-up　data　is　difficult　to　obtain　in　its　entirety.　To　this　end,　this　paper　proposes　a　local　convolutional　neural　network　(CNN)　based　pop-up　text　sub-recognition　algorithm.　Finally,　the　fuzzed　data　is　reconstructed　into　a　data　look-up　table　and　the　contents　of　the　data　look-up　table　are　formatted　for　output.　The　results　of　this　text　classification　and　recognition　algorithm　are　compared　with　those　of　four　commonly　used　domestic　and　international　search　engines　by　subjective　evaluation　method,　and　the　proposed　text　classification　and　recognition　algorithm　is　found　to　be　advanced.　World　Scientific　Publishing　Company.