Conference paper Open Access

Cognitive Content Recommendation in Digital Knowledge Repositories – a Survey of Recent Trends

Andrzej M.J. Skulimowski


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{
  "description": "<p>This paper presents an overview of the cognitive aspects of content recommendation process in large heterogeneous knowledge repositories. It also covers applications to design algorithms of incremental learning of users\u2019 prefe\u00adrences, emotions, and satisfaction. This allows the recommendation procedures to align to the present and expected cognitive states of a user, increasing combi\u00adned recommendation and repository use efficiency. The learning algorithm takes into account the results of the cognitive and neural modelling of users\u2019 decision behaviour. Inspirations from nature used in recommendation systems differ from the usual mimicking of biological neural processes. Specifically, a\u00a0cognitive knowledge recommender may follow a strategy to discover emotio\u00adnal patterns in user behaviour and then adjust the recommendation procedure accordingly. The knowledge of cognitive decision mechanisms helps to optimi\u00adze recommendation goals. Other cognitive recommendation procedures assist users in creating consistent learning or research groups. The anticipated primary application field of the above algorithms is a large knowledge repository coupled with an innovative training platform developed within the ongoing Horizon 2020 research project MOVING.</p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "Progress & Business Foundation; AGH University of Science and Technology", 
      "@id": "https://orcid.org/0000-0003-0646-2858", 
      "@type": "Person", 
      "name": "Andrzej M.J. Skulimowski"
    }
  ], 
  "headline": "Cognitive Content Recommendation in Digital Knowledge Repositories \u2013 a Survey of Recent Trends", 
  "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", 
  "datePublished": "2017-06-11", 
  "keywords": [
    "Research recommenders, scientific big data, Personal Learning Environments, preference modelling, mobile and ubiquitous learning"
  ], 
  "url": "https://zenodo.org/record/1059011", 
  "@type": "ScholarlyArticle", 
  "contributor": [
    {
      "affiliation": "AGH UST; P&BF", 
      "@id": "https://orcid.org/0000-0003-0646-2858", 
      "@type": "Person", 
      "name": "Andrzej M.J. Skulimowski"
    }
  ], 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.1007/978-3-319-59060-8_52", 
  "@id": "https://doi.org/10.1007/978-3-319-59060-8_52", 
  "workFeatured": {
    "url": "http://www.icaisc.org", 
    "alternateName": "ICAISC", 
    "location": "Zakopane, Poland", 
    "@type": "Event", 
    "name": "The 16th International Conference on Artificial Intelligence and Soft Computing"
  }, 
  "name": "Cognitive Content Recommendation in Digital Knowledge Repositories \u2013 a Survey of Recent Trends"
}
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