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Auflistung nach Autor:in "Endres, Markus"

1 - 5 von 5
  • Textdokument
    The Borda Social Choice Movie Recommender
    (BTW 2019, 2019) Kastner, Johannes; Ranitovic, Nemanja; Endres, Markus
    In this demo paper we present a recommender system, which exploits the Borda social choice voting rule for clustering recommendations in order to produce comprehensible results for a user. Considering existing clustering techniques like k-means, the overhead of normalizing and preparing the preferred user data is dropped. In our demo showcase we facilitate a comparison of our clustering approach to the well known k-means++ with traditional distance measures.
  • Konferenzbeitrag
    Personalized Stream Analysis with PreferenceSQL
    (Datenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband, 2017) Rudenko, Lena; Endres, Markus
    In this paper we present our demo application which allows preference-based search for interesting information in a data stream. In contrast to existing stream analysis services, the applica- tion uses the attributes of the stream records in combination with soft conditions to achieve the best possible result for a query.
  • Konferenzbeitrag
    Preference Analytics in EXASolution
    (Datenbanksysteme für Business, Technologie und Web (BTW 2015), 2015) Mandl, Stefan; Kozachuk, Oleksandr; Endres, Markus; Kießling, Werner
    Skyline queries and the more general concept of preferences are wellknown in the database community and there are many academic approaches for the computation of the best-matching objects. Furthermore, data analytics and multicriteria optimization play an important role in Business Intelligence where it facilitates optimal decision making. Preference Analytics is the combination of preferences and data analytics. SKYLINE is EXASOL's implementation of Preference Analytics in its commercial database management system EXASOLUTION. In this paper, we present SKYLINE from a user's perspective, describe algorithmic design decisions, and discuss its implementation in a distributed and parallel environment. The paper closes with an empirical evaluation of the system based on a number of preference queries over the TPC-H dataset using different scale factors.
  • Konferenzbeitrag
    Unsere Empfehlung für Sie: Präferenzen und Personalisierung in der Informatik
    (Informatik 2016, 2016) Endres, Markus; Pfandler, Andreas
  • Konferenzbeitrag
    Workshop Präferenzen und Personalisierung in der Informatik (PPI17)
    (Datenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband, 2017) Endres, Markus; Pfandler, Andreas