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  "Title": "Genetic Similarity in User-Based Collaborative Filtering",
  "Version": "1.0",
  "Date": "2019-12-08",
  "Encoding": "UTF-8",
  "Author": "Farimah Houshmand Nanehkaran, Seyed Mohammad Reza Lajevardi\n<R.Lajevardi@iaukashan.ac.ir>, Mahmoud Mahlouji Bidgholi\n<m.mahlouji@iaukashan.ac.ir>",
  "Maintainer": "Farimah Houshmand Nanehkaran <hoshmandcomputer@gmail.com>",
  "Description": "The genetic algorithm can be used directly to find the\nsimilarity of users and more effectively to increase the\nefficiency of the collaborative filtering method. By\nidentifying the nearest neighbors to the active user, before\nthe genetic algorithm, and by identifying suitable starting\npoints, an effective method for user-based collaborative\nfiltering method has been developed. This package uses an\noptimization algorithm (continuous genetic algorithm) to\ndirectly find the optimal similarities between active users\n(users for whom current recommendations are made) and others.\nFirst, by determining the nearest neighbor and their number,\nthe number of genes in a chromosome is determined. Each gene\nrepresents the neighbor's similarity to the active user. By\nestimating the starting points of the genetic algorithm, it\nquickly converges to the optimal solutions. The positive point\nis the independence of the genetic algorithm on the number of\ndata that for big data is an effective help in solving the\nproblem.",
  "License": "GPL (>= 2)",
  "RoxygenNote": "7.0.1",
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  "Packaged": {
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    "User": "root"
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  "Repository": "https://hoshmandcomputer.r-universe.dev",
  "Date/Publication": "2019-12-20 12:50:11 UTC",
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    {
      "page": "GACFF-package",
      "title": "Genetic Similarity in User-Based Collaborative Filtering",
      "topics": [
        "GACFF-package"
      ]
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    {
      "page": "Genetic",
      "title": "The genetic algorithm for finding similarities between users.",
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        "Genetic"
      ]
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      "title": "A set of Items id for recommending to an active user.",
      "topics": [
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