Reconstruction　of　Cross-Cut　Shredded　Text　Documents　(RCCSTD)　plays　an　important　role　in　both　forensics　and　archeology.　It　is　a　special　case　of　the　square　jigsaw　puzzle　problem　and　has　attracted　the　attention　of　many　researchers.　In　the　light　of　the　low　accuracy　of　existing　RCCSTD　solutions,　especially　regarding　row　splicing,　this　paper　proposes　a　high　accuracy　splicing　solution　by　using　both　a　combination　strategy　and　a　divide-and-conquer　strategy.　Unlike　other　approaches　based　on　the　Swarm　Intelligence　Algorithm,　where　the　results　and　splicing　accuracy　are　bound　up　with　the　defined　cost　function　and　the　number　of　fragments,　in　this　case　a　clustering　algorithm　was　used　to　transform　a　single　RCCSTD　problem　into　several　Reconstruction　of　Strip　Shredded　Text　Document　(RSSTD)　problems.　The　dual　combination　and　divide-and-conquer　strategies　proposed　in　this　paper　are　designed　to　improve　the　splicing　accuracy　in　a　row　and　make　the　algorithm　more　stable　as　the　number　of　fragments　in　a　row　increases.　Experiments　were　carried　out　on　10　text　documents　(5　Chinese　and　5　English),　which　were　shredded　into　ten　patterns.　The　returned　accuracy　measures　were　over　0.95　for　the　Chinese　documents　and　over　0.85　for　the　English　ones,　across　all　patterns.　A　comparison　is　made　between　our　approach　and　another　recently　proposed　solution,　and　we　conclude　that　our　approach　gives　both　higher　splicing　accuracy　and　greater　stability　regardless　of　the　number　of　fragments　in　a　row.