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Bio-ML: Machine Learning-Friendly Biomedical Datasets for Equivalence and Subsumption Ontology Matching.

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FarsBase: The Persian knowledge graph., , and . Semantic Web, 10 (6): 1169-1196 (2019)Interpolation-friendly B-trees: Bridging the Gap Between Algorithmic and Learned Indexes., and . EDBT, page 710-713. OpenProceedings.org, (2019)FarsBase: A Cross-Domain Farsi knowledge Graph., , and . SEMANTiCS (Posters & Demos), volume 2198 of CEUR Workshop Proceedings, CEUR-WS.org, (2018)ROLL: Fast In-Memory Generation of Gigantic Scale-free Networks., , , and . SIGMOD Conference, page 1829-1842. ACM, (2016)Charset Encoding Detection of HTML Documents - A Practical Experience., , and . AIRS, volume 9460 of Lecture Notes in Computer Science, page 215-226. Springer, (2015)FLIRT: A Fast Learned Index for Rolling Time frames., , , and . EDBT, page 234-246. OpenProceedings.org, (2023)Bio-ML: Machine Learning-Friendly Biomedical Datasets for Equivalence and Subsumption Ontology Matching., , , , , and . (July 2023)Clustering Based Multi-Objective Rule Mining using Genetic Algorithm., , and . JDCTA, 4 (1): 37-42 (2010)An Empirical Study on the Effect of Morphological and Lexical Features in Persian Dependency Parsing., , and . SPMRL@EMNLP, page 97-107. Association for Computational Linguistics, (2013)Machine Learning-Friendly Biomedical Datasets for Equivalence and Subsumption Ontology Matching., , , , , and . (July 2022)