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  "Description": "Provides Bayesian probabilistic methods for record linkage\nand entity resolution across multiple datasets using the\nComprehensive Hit Or Miss Probabilistic Entity Resolution\n(CHOMPER) model. The package implements three main inference\napproaches: (1) Evolutionary Variational Inference for record\nLinkage (EVIL), (2) Coordinate Ascent Variational Inference\n(CAVI), and (3) Markov Chain Monte Carlo (MCMC) with split and\nmerge process. The model supports both discrete and continuous\nfields, and it performs locally-varying hit mechanism for the\nattributes with multiple truths. It also provides tools for\nperformance evaluation based on either approximated variational\nfactors or posterior samples. The package is designed to\nsupport parallel computing with multi-threading support for\nEVIL to estimate the linkage structure faster.",
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        "chomper"
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      "title": "CHOMPER with Evolutionary Variational Inference for Record Linkage",
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