• Network Graph as a Musical Instrument

    Music can be visualized as a graph. While there are many ways to do that, one of the possibilities is to represent the notes (and octaves) as the nodes and their co-occurrences as the connections between them. This representation allows us to reveal patterns in our composition and to use the powerful graph theory algorithms to uncover interesting insights about the structure of the music we’re playing.

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  • “The Game” and Social Dynamics of Pick-Up Artists

    Basic principles of network operation can be successfully used for establishing a new kind of ethics for social encounters. We look at the social dynamics modulated through so-called “Game” utilized by pick-up artists and abstract this approach to learn interesting new behaviors for activating intersubjective relations.

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  • Using Efficient Search Methods for Content Structuring

    Designing efficient content structures that guide readers through in ways that are efficient, maintaining diversity and narrative of the original.

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  • Divinatory Recommender Systems: between Similarity and Serendipity

    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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  • Knowledge Graphs: The New Type of Document for the 21st Century

    Excel was a revolutionary product for the time, but in the 21st century columns and rows are not sufficient anymore. What matters today are multidimensional relations between data, which combine a better view of the bigger picture with an attention to detail: networks and graphs.

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