{
  "id": "1411.6850",
  "version": "v1",
  "published": "2014-11-25T13:13:47.000Z",
  "updated": "2014-11-25T13:13:47.000Z",
  "title": "Similarity- based approach for outlier detection",
  "authors": [
    "Amina Dik",
    "Khalid Jebari",
    "Abdelaziz Bouroumi",
    "Aziz Ettouhami"
  ],
  "comment": "International Journal of Computer Science Issues 2014",
  "categories": [
    "cs.CV"
  ],
  "abstract": "This paper presents a new approach for detecting outliers by introducing the notion of object's proximity. The main idea is that normal point has similar characteristics with several neighbors. So the point in not an outlier if it has a high degree of proximity and its neighbors are several. The performance of this approach is illustrated through real datasets",
  "revisions": [
    {
      "version": "v1",
      "updated": "2014-11-25T13:13:47.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "outlier detection",
      "real datasets",
      "high degree",
      "similar characteristics",
      "objects proximity"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable",
      "adsabs": "2014arXiv1411.6850D"
    }
  }
}