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Auflistung nach Autor:in "Spranger, Michael"

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  • Zeitschriftenartikel
    Evolving Grounded Spatial Language Strategies
    (KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013) Spranger, Michael
    Each natural language phrase is evidence for a particular strategy of construing reality. One domain where this has been extensively studied is spatial language, which reveals an enormous amount of variation of conceptualization strategies both within a particular language and cross-culturally. This paper proposes a computational formalism for representing conceptualization strategies and shows how the formalism can be used to study and explain the evolution and emergence of spatial conceptualization strategies and their impact on shared grounded communication systems.
  • Zeitschriftenartikel
    MoNA: A Forensic Analysis Platform for Mobile Communication
    (KI - Künstliche Intelligenz: Vol. 36, No. 2, 2022) Spranger, Michael; Xi, Jian; Jaeckel, Lukas; Felser, Jenny; Labudde, Dirk
    Mobile communication devices are a popular means of planning, commissioning and carrying out criminal offenses. In particular, data from messengers such as WhatsApp or Telegram often contain conclusive information. Organized crime also usually involves many devices, but not all of them contain the full history of communication. Rather, it is heavily fragmented due to individual deletions of messages or different joining times to groups. A singular evaluation of individual devices is therefore often not expedient, since important relationships cannot be recognized. Furthermore, communication is often distributed across different channels and modalities and can only be fully and correctly understood through a joint semantic analysis. The linking of related communications of different devices enables an almost complete reconstruction of the communication with a simultaneous reduction in reading effort by merging identical messages. Grouping coherent messages into conversations enables efficient comparison with a knowledge model. Building such a model is complex, but can be supported by a term recommender system. In this paper, MoNA is presented as a platform that implements these approaches and enables an assisted analysis of mobile communications.
  • Konferenzbeitrag
    Semi-supervised topic modelling as a tool for hypothesis-driven forensic communication analysis
    (INFORMATIK 2024, 2024) Felser, Jenny; Spranger, Michael
    Mobile communication data has become a crucial source of evidence in digital forensics. Nevertheless, the high volume of chat messages presents a challenge for investigators, mainly as only a tiny fraction is relevant to the case. Therefore, a method is needed to summarise the messages in a way that separates the forensically relevant parts from the irrelevant ones. Topic modelling can be beneficial as it automatically extracts the main ideas of the chats. However, more than traditional unsupervised topic modelling is needed for forensic data analysis as it is inherently hypothesis-driven. This research incorporates case-specific knowledge into topic modelling to extract topics that align with the investigator’s expectations. Two semi-supervised topic modelling algorithms and proposed extensions were compared using real-case data. The user study results suggested extending algorithms based on word embeddings could help find evidence for suspected topics. Furthermore, the study examined the correlation between these findings and topic coherence, a standard measure of automatic evaluation that did not reflect actual interpretability.