Researchers have developed new depth-first representations for $k^2$-trees to improve their efficiency and compression, addressing the poor cache performance of traditional level-wise layouts. The proposed methods, including EDF-1, BP, CEDF, and CBP, utilize depth-first layouts and a linear-time compression technique for identical subtrees. Experimental results on web graphs, Wikidata, and synthetic data show that these new representations are competitive, with CEDF offering the best compression and EDF-1/CEDF consistently reducing peak memory usage, leading to improved performance in matrix operations. AI
RANK_REASON Academic paper detailing new data structure representations and experimental evaluation. [lever_c_demoted from research: ic=1 ai=0.4]
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