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Auflistung nach Autor:in "Bauckhage, Christian"

1 - 9 von 9
  • Zeitschriftenartikel
    Can Computers Learn from the Aesthetic Wisdom of the Crowd?
    (KI - Künstliche Intelligenz: Vol. 27, No. 1, 2013) Bauckhage, Christian; Kersting, Kristian
    The social media revolution has led to an abundance of image and video data on the Internet. Since this data is typically annotated, rated, or commented upon by large communities, it provides new opportunities and challenges for computer vision. Social networking and content sharing sites seem to hold the key to the integration of context and semantics into image analysis. In this paper, we explore the use of social media in this regard. We present empirical results obtained on a set of 127,593 images with 3,741,176 tag assignments that were harvested from Flickr, a photo sharing site. We report on how users tag and rate photos and present an approach towards automatically recognizing the aesthetic appeal of images using confidence-based classifiers to alleviate effects due to ambiguously labeled data. Our results indicate that user generated content allows for learning about aesthetic appeal. In particular, established low-level image features seem to enable the recognition of beauty. A reliable recognition of unseemliness, on the other hand, appears to require more elaborate high-level analysis.
  • Zeitschriftenartikel
    Data Mining and Pattern Recognition in Agriculture
    (KI - Künstliche Intelligenz: Vol. 27, No. 4, 2013) Bauckhage, Christian; Kersting, Kristian
    Modern communication, sensing, and actuator technologies as well as methods from signal processing, pattern recognition, and data mining are increasingly applied in agriculture. Developments such as increased mobility, wireless networks, new environmental sensors, robots, and the computational cloud put the vision of a sustainable agriculture for anybody, anytime, and anywhere within reach. Yet, precision farming is a fundamentally new domain for computational intelligence and constitutes a truly interdisciplinary venture. Accordingly, researchers and experts of complementary skills have to cooperate in order to develop models and tools for data intensive discovery that allow for operation through users that are not necessarily trained computer scientists. We present approaches and applications that address these challenges and underline the potential of data mining and pattern recognition in agriculture.
  • Konferenzbeitrag
    Group evolution patterns in world of warcraft
    (INFORMATIK 2010. Service Science – Neue Perspektiven für die Informatik. Band 2, 2010) Thurau, Christian; Bauckhage, Christian
    We study the temporal evolution of different types of guilds in the massively multiplayer online role playing game WORLD OF WARCRAFT®. Given a large corpus of observations of online activities of players, we apply convex-hull non-negative matrix factorization to cluster our data of about 1,400,000 guilds into well interpretable prototypes. Given these prototypes, we analyze guild formation patterns on American and European servers. We find growth patterns according to power laws that result in similar structures in both cases.
  • Zeitschriftenartikel
    Growing Executable Code-Quality-Knowledge Organically
    (Softwaretechnik-Trends Band 38, Heft 2, 2018) Speichewr, Daniel; Dong, Tiansi; Bauckhage, Christian; Cremers, Armin B.
  • Zeitschriftenartikel
    Künstliche Intelligenz für Computerspiele
    (Informatik-Spektrum: Vol. 37, No. 6, 2014) Bauckhage, Christian; Kersting, Kristian; Thurau, Christian
    Die technische Entwicklung von Computerspielen und die Entwicklung von Methoden der Künstlichen Intelligenz (KI) gehen seit Jahrzehnten Hand in Hand. Spektakuläre Erfolge der KI in Spieleszenarien sind etwa der Sieg des Schachcomputers Deep Blue über den damaligen Weltmeister Gary Kasparow im Jahr 1997 oder der Gewinn der Quizshow Jeopardy durch das Programm Watson im Jahr 2010. Standen lange Zeit Fragen zur Implementierung möglichst intelligenter und glaubwürdiger künstlicher Spieler im Vordergrund, ergeben sich durch aktuelle Entwicklungen in den Bereichen mobile- und social gaming neue Problemstellungen für die KI. Dieser Artikel beleuchtet die historische Entwicklung der KI in Computerspielen und diskutiert die Herausforderungen, die sich in modernen Spieleszenarien ergeben.
  • Zeitschriftenartikel
    Learning Human Behavior from Analyzing Activities in Virtual Environments
    (MMI Interaktiv - Human: Vol. 1, No. 12, 2007) Bauckhage, Christian; Gorman, Bernard; Thurau, Christian; Humphrys, Mark
    Present day multiplayer video games offer an interesting perspective for researching artificial cognitive systems. In this contribution, we focus on the problem of learning believable behavior models for artificial characters. Recordings of the network traffic of modern games allow for applying machine learning techniques to realize artificial agents that act more human-like than conventional current game characters. We detail an imitation learning approach and present the results of an extensive believability study that was carried out on the Internet.
  • Zeitschriftenartikel
    Matrix- and Tensor Factorization for Game Content Recommendation
    (KI - Künstliche Intelligenz: Vol. 34, No. 1, 2020) Sifa, Rafet; Yawar, Raheel; Ramamurthy, Rajkumar; Bauckhage, Christian; Kersting, Kristian
    Commercial success of modern freemium games hinges on player satisfaction and retention. This calls for the customization of game content or game mechanics in order to keep players engaged. However, whereas game content is already frequently generated using procedural content generation, methods that can reliably assess what kind of content suits a player’s skills or preferences are still few and far between. Addressing this challenge, we propose novel recommender systems based on latent factor models that allow for recommending quests in a single player role-playing game. In particular, we introduce a tensor factorization algorithm to decompose collections of bipartite matrices which represent how players’ interests and behaviors change over time. Extensive online bucket type tests during the ongoing operation of a commercial game reveal that our system is able to recommend more engaging quests and to retain more players than previous handcrafted or collaborative filtering approaches.
  • Konferenzbeitrag
    Notes on the Code Quality Culture on Jupyter (Notebooks)
    (Softwaretechnik-Trends Band 39, Heft 2, 2019) Speicher, Daniel; Dong, Tiansi; Cremers, Olaf; Bauckhage, Christian; Cremers, Armin B.
    While we argued in that code quality needs to take context into account, there is now software that demands a really different quality culture like we would be entering another planet. Jupyter, to be precise: A “Jupyter Notebook is [a] web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text.” It consists of text and code cells. The content of code cells is sent on demand to a Python session, executed and the output inserted below the cell. We will approach the quality of notebooks from the perspective of communicative code and design patterns.
  • Zeitschriftenartikel
    Sicherheit von Quantum Machine Learning
    (Wirtschaftsinformatik & Management: Vol. 14, No. 2, 2022) Sultanow, Eldar; Bauckhage, Christian; Knopf, Christian; Piatkowski, Nico