July 30, 2020 Journal article Open Access

Vidhyavani.A; Pooja Gopi; Sushil Ram; Sujay Sukumar

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    "name": "English"
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      "@type": "CreativeWork"
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    {
      "@id": "https://hdl.handle.net/B3372079220/2020\u00a9BEIESP", 
      "@type": "CreativeWork"
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  "description": "<p>This application starter work in the region of site page expectation is introduced. The structured and actualized model offers customized association by anticipating the client&#39;s conduct from past web perusing history. Those forecasts are a short time later used to streamline the client&#39;s future connections. We propose a Profile-based Interaction Prediction Framework (PIPF), which can illuminate the occasion activated connection expectation issue productively and adequately. In PIPF, we initially change the cooperation sign into a Sliding-window Evolving Graph (SEG) to decrease the information volume and steadily update SEG as the association log develops. At that point, we construct profiles intended to introduce clients&#39; conduct by separating the static and astounding highlights from SEG. The static (separately, astonishing) stress mirrors the normality of clients&#39; conduct (individually, the transient conduct). At the point when an occasion happens, we process the closeness between the event and every competitor connects.</p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "Computer science, SRM Institute of science and  Technology, Chennai, India,", 
      "@type": "Person", 
      "name": "Vidhyavani.A"
    }, 
    {
      "affiliation": "Computer science, SRM Institute of science and  Technology, Chennai, India,", 
      "@type": "Person", 
      "name": "Pooja Gopi"
    }, 
    {
      "affiliation": "Computer science, SRM Institute of science and  Technology, Chennai, India,", 
      "@type": "Person", 
      "name": "Sushil Ram"
    }, 
    {
      "affiliation": "Computer science, SRM Institute of science and  Technology, Chennai, India,", 
      "@type": "Person", 
      "name": "Sujay Sukumar"
    }
  ], 
  "headline": "Adaptive Prediction of User Interaction based on  Deep Learning", 
  "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", 
  "datePublished": "2020-07-30", 
  "keywords": [
    "Deep learning, gated recurrent unit (GRU), Navigation prediction, user interaction, web applications."
  ], 
  "url": "https://zenodo.org/record/5852593", 
  "contributor": [
    {
      "affiliation": "Publisher", 
      "@type": "Person", 
      "name": "Blue Eyes Intelligence Engineering  and Sciences Publication(BEIESP)"
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  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.35940/ijrte.B3372.079220", 
  "@id": "https://doi.org/10.35940/ijrte.B3372.079220", 
  "@type": "ScholarlyArticle", 
  "name": "Adaptive Prediction of User Interaction based on  Deep Learning"
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