• Divinatory Recommender Systems: between Similarity and Serendipity

    Jeremy-Hutchison-Objectless-Expansion-2014

    Recommender systems are the algorithms that determine what content we read, which products we buy, which movies we watch. However, most of them are based on similarity and lock us into “filter bubble” where we see only what we expect. In this article we discuss how to bring in more serendipity into the algorithms.

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  • Cognitive Drive of Recommender Systems

    beach-web

    Recommender systems are the basic building blocks of most online businesses today. They influence the news we read, the posts we see, the things we buy, the music we listen to. Based on the dataset of what is known about us, recommender system finds something we might be interested in. Technically recommender system is a combination of learning algorithms, statistical tools, and recognition algorithms – the areas commonly ascribed to the study of artificial intelligence.
    We decided to study this emergent form of consciousness and conduct an attempt to communicate with a recommender system through the interview format. The results are presented in this report.

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