TY - CHAP A1 - Büsgen, André A1 - Klöser, Lars A1 - Kohl, Philipp A1 - Schmidts, Oliver A1 - Kraft, Bodo A1 - Zündorf, Albert T1 - Exploratory analysis of chat-based black market profiles with natural language processing T2 - Proceedings of the 11th International Conference on Data Science, Technology and Applications N2 - Messenger apps like WhatsApp or Telegram are an integral part of daily communication. Besides the various positive effects, those services extend the operating range of criminals. Open trading groups with many thousand participants emerged on Telegram. Law enforcement agencies monitor suspicious users in such chat rooms. This research shows that text analysis, based on natural language processing, facilitates this through a meaningful domain overview and detailed investigations. We crawled a corpus from such self-proclaimed black markets and annotated five attribute types products, money, payment methods, user names, and locations. Based on each message a user sends, we extract and group these attributes to build profiles. Then, we build features to cluster the profiles. Pretrained word vectors yield better unsupervised clustering results than current state-of-the-art transformer models. The result is a semantically meaningful high-level overview of the user landscape of black market chatrooms. Additionally, the extracted structured information serves as a foundation for further data exploration, for example, the most active users or preferred payment methods. KW - Clustering KW - Natural Language Processing KW - Information Extraction KW - Profile Extraction KW - Text Mining Y1 - 2022 SN - 978-989-758-583-8 U6 - http://dx.doi.org/10.5220/0011271400003269 SN - 2184-285X SP - 83 EP - 94 ER - TY - CHAP A1 - Büsgen, André A1 - Klöser, Lars A1 - Kohl, Philipp A1 - Schmidts, Oliver A1 - Kraft, Bodo A1 - Zündorf, Albert ED - Cuzzocrea, Alfredo ED - Gusikhin, Oleg ED - Hammoudi, Slimane ED - Quix, Christoph T1 - From cracked accounts to fake IDs: user profiling on German telegram black market channels T2 - Data Management Technologies and Applications N2 - Messenger apps like WhatsApp and Telegram are frequently used for everyday communication, but they can also be utilized as a platform for illegal activity. Telegram allows public groups with up to 200.000 participants. Criminals use these public groups for trading illegal commodities and services, which becomes a concern for law enforcement agencies, who manually monitor suspicious activity in these chat rooms. This research demonstrates how natural language processing (NLP) can assist in analyzing these chat rooms, providing an explorative overview of the domain and facilitating purposeful analyses of user behavior. We provide a publicly available corpus of annotated text messages with entities and relations from four self-proclaimed black market chat rooms. Our pipeline approach aggregates the extracted product attributes from user messages to profiles and uses these with their sold products as features for clustering. The extracted structured information is the foundation for further data exploration, such as identifying the top vendors or fine-granular price analyses. Our evaluation shows that pretrained word vectors perform better for unsupervised clustering than state-of-the-art transformer models, while the latter is still superior for sequence labeling. KW - Clustering KW - Natural language processing KW - Information extraction KW - Profile extraction KW - Text mining Y1 - 2023 SN - 978-3-031-37889-8 (Print) SN - 978-3-031-37890-4 (Online) U6 - http://dx.doi.org/10.1007/978-3-031-37890-4_9 N1 - 10th International Conference, DATA 2021, Virtual Event, July 6–8, 2021, and 11th International Conference, DATA 2022, Lisbon, Portugal, July 11-13, 2022 SP - 176 EP - 202 PB - Springer CY - Cham ER - TY - JOUR A1 - Hacker, Tobias A1 - Kraft, Bodo A1 - Zöll, Axel T1 - Projektzuschnitt für die inkrementelle Systementwicklung im Konzernverbund Y1 - 2011 SN - 978-3-8322-9990-3 N1 - Zusammenspiel von Vorgehensmodellen und Organisationsformen, Workshop der Fachgruppe WI-VM der Gesellschaft für Informatik, 18 SP - 78 EP - 83 ER - TY - CHAP A1 - Heer, Thomas A1 - Redkowitz, Daniel A1 - Kraft, Bodo T1 - Tool Support for the Integration of Light-Weight Ontologies N2 - Abstract of the authors: In many areas of computer science ontologies become more and more important. The use of ontologies for domain modeling often brings up the issue of ontology integration. The task of merging several ontologies, covering specific subdomains, into one united ontology has to be solved. Many approaches for ontology integration aim at automating the process of ontology alignment. However, a complete automation is not feasible, and user interaction is always required. Nevertheless, most ontology integration tools offer only very limited support for the interactive part of the integration process. In this paper, we present a novel approach for the interactive integration of ontologies. The result of the ontology integration is incrementally updated after each definition of a correspondence between ontology elements. The user is guided through the ontologies to be integrated. By restricting the possible user actions, the integrity of all defined correspondences is ensured by the tool we developed. We evaluated our tool by integrating different regulations concerning building design. KW - Ontologie KW - Knowledge Management KW - Ontology Engineering KW - Information Integration Tools KW - Human Factors Y1 - 2008 SN - 978-3-642-00670-8 ER - TY - CHAP A1 - Kirchhof, M. A1 - Kraft, Bodo T1 - UML-based modeling of architectural knowledge and design N2 - IASSE-2004 - 13th International Conference on Intelligent and Adaptive Systems and Software Engineering eds. W. Dosch, N. Debnath, pp. 245-250, ISCA, Cary, NC, 1-3 July 2004, Nice, France We introduce a UML-based model for conceptual design support in civil engineering. Therefore, we identify required extensions to standard UML. Class diagrams are used for elaborating building typespecific knowledge: Object diagrams, implicitly contained in the architect’s sketch, are validated against the defined knowledge. To enable the use of industrial, domain-specific tools, we provide an integrated conceptual design extension. The developed tool support is based on graph rewriting. With our approach architects are enabled to deal with semantic objects during early design phase, assisted by incremental consistency checks. KW - UML KW - UML KW - Unified Modeling Language KW - UML KW - Unified Modeling Language Y1 - 2004 ER - TY - JOUR A1 - Kirchhof, Michael A1 - Kraft, Bodo T1 - Hybrides Vorgehensmodell : Agile und klassische Methoden im Projekt passend kombinieren JF - ProjektMagazin N2 - Agil ist im Trend und immer mehr Unternehmen, die ihre Projekte bisher nach klassischen Prinzipien durchführten, denken über den Einsatz agiler Methoden nach. Doch selbst wenn die Organisation bereits beide Philosophien unterstützt, gilt für ein Projekt meist die klare Vorgabe: agil oder klassisch. Es gibt aber noch einen anderen Ansatz, mit diesen "unterschiedlichen Welten" umzugehen: Und zwar die beiden Philosophien innerhalb eines Projekts zu kombinieren. Wie dies in der Praxis aussehen und gelingen kann, zeigen Dr. Michael Kirchhof und Prof. Dr. Bodo Kraft in diesem Beitrag. Y1 - 2012 IS - 11 SP - 11 S. PB - Berleb Media CY - Taufkirchen ER - TY - CHAP A1 - Kirchhof, Michael A1 - Kraft, Bodo T1 - Dogmatisches „Entweder agil oder klassisch" im Projektmanagement hat ausgedient - die richtige Mischung macht's T2 - Projekt-Sternstunden : strahlende Erfolge durch Kompetenz Y1 - 2011 SN - 978-3-924841-60-7 N1 - PM-Forum <28, 2011, Nürnberg> ; PM-Forum 2011, 28. Internationales Deutsches Projektmanagement-Forum ; Nürnberg, 25. - 26.10.2011 ; Tagungsband SP - 414 EP - 425 PB - GPM CY - Nürnberg ER - TY - CHAP A1 - Klöser, Lars A1 - Büsgen, André A1 - Kohl, Philipp A1 - Kraft, Bodo A1 - Zündorf, Albert ED - Conte, Donatello ED - Fred, Ana ED - Gusikhin, Oleg ED - Sansone, Carlo T1 - Explaining relation classification models with semantic extents T2 - DeLTA 2023: Deep Learning Theory and Applications N2 - In recent years, the development of large pretrained language models, such as BERT and GPT, significantly improved information extraction systems on various tasks, including relation classification. State-of-the-art systems are highly accurate on scientific benchmarks. A lack of explainability is currently a complicating factor in many real-world applications. Comprehensible systems are necessary to prevent biased, counterintuitive, or harmful decisions. We introduce semantic extents, a concept to analyze decision patterns for the relation classification task. Semantic extents are the most influential parts of texts concerning classification decisions. Our definition allows similar procedures to determine semantic extents for humans and models. We provide an annotation tool and a software framework to determine semantic extents for humans and models conveniently and reproducibly. Comparing both reveals that models tend to learn shortcut patterns from data. These patterns are hard to detect with current interpretability methods, such as input reductions. Our approach can help detect and eliminate spurious decision patterns during model development. Semantic extents can increase the reliability and security of natural language processing systems. Semantic extents are an essential step in enabling applications in critical areas like healthcare or finance. Moreover, our work opens new research directions for developing methods to explain deep learning models. KW - Relation classification KW - Natural language processing KW - Natural language understanding KW - Information extraction KW - Trustworthy artificial intelligence Y1 - 2023 SN - 978-3-031-39058-6 (Print) SN - 978-3-031-39059-3 (Online) U6 - http://dx.doi.org/10.1007/978-3-031-39059-3_13 N1 - 4th International Conference, DeLTA 2023, Rome, Italy, July 13–14, 2023. SP - 189 EP - 208 PB - Springer CY - Cham ER - TY - CHAP A1 - Klöser, Lars A1 - Kohl, Philipp A1 - Kraft, Bodo A1 - Zündorf, Albert T1 - Multi-attribute relation extraction (MARE): simplifying the application of relation extraction T2 - Proceedings of the 2nd International Conference on Deep Learning Theory and Applications - DeLTA N2 - Natural language understanding’s relation extraction makes innovative and encouraging novel business concepts possible and facilitates new digitilized decision-making processes. Current approaches allow the extraction of relations with a fixed number of entities as attributes. Extracting relations with an arbitrary amount of attributes requires complex systems and costly relation-trigger annotations to assist these systems. We introduce multi-attribute relation extraction (MARE) as an assumption-less problem formulation with two approaches, facilitating an explicit mapping from business use cases to the data annotations. Avoiding elaborated annotation constraints simplifies the application of relation extraction approaches. The evaluation compares our models to current state-of-the-art event extraction and binary relation extraction methods. Our approaches show improvement compared to these on the extraction of general multi-attribute relations. Y1 - 2021 SN - 978-989-758-526-5 U6 - http://dx.doi.org/10.5220/0010559201480156 N1 - Proceedings of the 2nd International Conference on Deep Learning Theory and Applications, DeLTA2021, July 7-9, 2021 SP - 148 EP - 156 ER - TY - CHAP A1 - Kohl, Philipp A1 - Freyer, Nils A1 - Krämer, Yoka A1 - Werth, Henri A1 - Wolf, Steffen A1 - Kraft, Bodo A1 - Meinecke, Matthias A1 - Zündorf, Albert ED - Conte, Donatello ED - Fred, Ana ED - Gusikhin, Oleg ED - Sansone, Carlo T1 - ALE: a simulation-based active learning evaluation framework for the parameter-driven comparison of query strategies for NLP T2 - Deep Learning Theory and Applications. DeLTA 2023. Communications in Computer and Information Science N2 - Supervised machine learning and deep learning require a large amount of labeled data, which data scientists obtain in a manual, and time-consuming annotation process. To mitigate this challenge, Active Learning (AL) proposes promising data points to annotators they annotate next instead of a subsequent or random sample. This method is supposed to save annotation effort while maintaining model performance. However, practitioners face many AL strategies for different tasks and need an empirical basis to choose between them. Surveys categorize AL strategies into taxonomies without performance indications. Presentations of novel AL strategies compare the performance to a small subset of strategies. Our contribution addresses the empirical basis by introducing a reproducible active learning evaluation (ALE) framework for the comparative evaluation of AL strategies in NLP. The framework allows the implementation of AL strategies with low effort and a fair data-driven comparison through defining and tracking experiment parameters (e.g., initial dataset size, number of data points per query step, and the budget). ALE helps practitioners to make more informed decisions, and researchers can focus on developing new, effective AL strategies and deriving best practices for specific use cases. With best practices, practitioners can lower their annotation costs. We present a case study to illustrate how to use the framework. KW - Active learning KW - Query learning KW - Natural language processing KW - Deep learning KW - Reproducible research Y1 - 2023 SN - 978-3-031-39058-6 (Print) SN - 978-3-031-39059-3 (Online) U6 - http://dx.doi.org/978-3-031-39059-3 N1 - 4th International Conference, DeLTA 2023, Rome, Italy, July 13–14, 2023. SP - 235 EP - 253 PB - Springer CY - Cham ER - TY - CHAP A1 - Kohl, Philipp A1 - Schmidts, Oliver A1 - Klöser, Lars A1 - Werth, Henri A1 - Kraft, Bodo A1 - Zündorf, Albert T1 - STAMP 4 NLP – an agile framework for rapid quality-driven NLP applications development T2 - Quality of Information and Communications Technology. QUATIC 2021 N2 - The progress in natural language processing (NLP) research over the last years, offers novel business opportunities for companies, as automated user interaction or improved data analysis. Building sophisticated NLP applications requires dealing with modern machine learning (ML) technologies, which impedes enterprises from establishing successful NLP projects. Our experience in applied NLP research projects shows that the continuous integration of research prototypes in production-like environments with quality assurance builds trust in the software and shows convenience and usefulness regarding the business goal. We introduce STAMP 4 NLP as an iterative and incremental process model for developing NLP applications. With STAMP 4 NLP, we merge software engineering principles with best practices from data science. Instantiating our process model allows efficiently creating prototypes by utilizing templates, conventions, and implementations, enabling developers and data scientists to focus on the business goals. Due to our iterative-incremental approach, businesses can deploy an enhanced version of the prototype to their software environment after every iteration, maximizing potential business value and trust early and avoiding the cost of successful yet never deployed experiments. KW - Machine learning KW - Process model KW - Natural language processing Y1 - 2021 SN - 978-3-030-85346-4 SN - 978-3-030-85347-1 U6 - http://dx.doi.org/10.1007/978-3-030-85347-1_12 N1 - International Conference on the Quality of Information and Communications Technology, QUATIC 2021, 8-11 September, Algarve, Portugal SP - 156 EP - 166 PB - Springer CY - Cham ER - TY - CHAP A1 - Kraft, Bodo T1 - Conceptual design tools for civil engineering N2 - Applications of Graph Transformations with Industrial Relevance Lecture Notes in Computer Science, 2004, Volume 3062/2004, 434-439, DOI: http://dx.doi.org/10.1007/978-3-540-25959-6_33 This paper gives a brief overview of the tools we have developed to support conceptual design in civil engineering. Based on the UPGRADE framework, two applications, one for the knowledge engineer and another for architects allow to store domain specific knowledge and to use this knowledge during conceptual design. Consistency analyses check the design against the defined knowledge and inform the architect if rules are violated. KW - CAD KW - CAD KW - Bauingenieurwesen KW - CAD KW - civil engineering Y1 - 2004 ER - TY - JOUR A1 - Kraft, Bodo T1 - Conceptual design mit ArchiCAD 8 : Forschungsprojekt an der RWTH Aachen N2 - Projektbericht in GraphisoftNews - Architektur und Bauen in einer vernetzten Welt 3/2003 4 Seiten KW - CAD KW - CAD KW - Bauingenieurwesen KW - Architektur KW - CAD KW - civil engineering KW - architecture Y1 - 2003 ER - TY - GEN A1 - Kraft, Bodo T1 - LexiCAD Step by Step : Bürogebäude : Erstellen eines Grundrisses mit RoomObjects und LexiCAD N2 - 11 Seiten, 22 Abbildungen 1. Konstruktion des Außenumrisses 2. Festlegung der inneren Räume 3. Einfügen der RoomLinks 4. Wallgenerator KW - CAD KW - CAD KW - Architektur KW - CAD KW - architecture Y1 - 2003 ER - TY - BOOK A1 - Kraft, Bodo T1 - Semantische Unterstützung des konzeptuellen Gebäudeentwurfs Y1 - 2007 SN - 978-3-8322-6045-3 N1 - Berichte aus der Informatik ; Zugl.: Aachen, Techn. Hochsch., Diss., 2007 PB - Shaker CY - Aachen ER - TY - JOUR A1 - Kraft, Bodo A1 - Heer, Thomas A1 - Retkowitz, Daniel T1 - Algorithm and Tool for Ontology Integration Based on Graph Rewriting / Heer, Thomas ; Retkowitz, Daniel ; Kraft, Bodo JF - Applications of Graph Transformations with Industrial Relevance / Third International Symposium, AGTIVE 2007, Kassel, Germany, October 10-12, 2007, Revised Selected and Invited Papers Y1 - 2008 SN - 978-3-540-89019-5 N1 - Lecture Notes in Computer Science ; 5088 SP - 577 EP - 582 ER - TY - JOUR A1 - Kraft, Bodo A1 - Heer, Thomas A1 - Retkowitz, Daniel T1 - Incremental Ontology Integration / Heer, Thomas ; Retkowitz, Daniel ; Kraft, Bodo JF - Proceedings of the 10th International Conference on Enterprise Information Systems : Barcelona, Spain, June 12 - 16, 2008 / organized by INSTICC, Institute for Systems and Technologies of Information, Control and Communication ... [Ed. by José Cordeiro ...] Y1 - 2008 N1 - International Conference on Enterprise Information Systems ; (10 : ; 2008.06.12-16 : ; Barcelona) ; ICEIS ; (10 : ; 2008.06.12-16 : ; Barcelona) SP - 13 EP - 28 PB - INSTICC CY - Setubal ER - TY - CHAP A1 - Kraft, Bodo A1 - Kohl, Philipp A1 - Meinecke, Matthias ED - Bernert, Christian ED - Scheurer, Steffen ED - Wehnes, Harald T1 - Analyse und Nachverfolgung von Projektzielen durch Einsatz von Natural Language Processing T2 - KI in der Projektwirtschaft : was verändert sich durch KI im Projektmanagement? Y1 - 2024 SN - 978-3-3811-1132-9 (Online) SN - 978-3-3811-1131-2 (Print) U6 - http://dx.doi.org/10.24053/9783381111329 SP - 157 EP - 167 PB - UVK Verlag ER - TY - CHAP A1 - Kraft, Bodo A1 - Meyer, Oliver A1 - Nagl, Manfred T1 - Graph technology support for conceptual design in civil engineering N2 - In: Advances in intelligent computing in engineering : proceedings of the 9.International EG-ICE Workshop ; Darmstadt, (01 - 03 August) 2002 / Martina Schnellenbach-Held ... (eds.) . - Düsseldorf: VDI-Verl., 2002 .- Fortschritt-Berichte VDI, Reihe 4, Bauingenieurwesen ; 180 ; S. 1-35 The paper describes a novel way to support conceptual design in civil engineering. The designer uses semantical tools guaranteeing certain internal structures of the design result but also the fulfillment of various constraints. Two different approaches and corresponding tools are discussed: (a) Visually specified tools with automatic code generation to determine a design structure as well as fixing various constraints a design has to obey. These tools are also valuable for design knowledge specialist. (b) Extensions of existing CAD tools to provide semantical knowledge to be used by an architect. It is sketched how these different tools can be combined in the future. The main part of the paper discusses the concepts and realization of two prototypes following the two above approaches. The paper especially discusses that specific graphs and the specification of their structure are useful for both tool realization projects. KW - CAD KW - CAD ; KW - CAD KW - civil engineering Y1 - 2002 SN - 3-18-318004-9 ER - TY - JOUR A1 - Kraft, Bodo A1 - Nagl, Manfred T1 - Visual Knowledge Specification for Conceptual Design: Definition and Tool Support N2 - In: Advanced Engineering Informatics. Vol 21, Issue 1, 2007, Pages 67-83 http://dx.doi.org/10.1016/j.aei.2006.10.001 eds. J.C. Kunz, I.F.C. Smith and T. Tomiyama, Elsevier, Seite 1-22 Current CAD tools are not able to support the conceptual design phase, and none of them provides a consistency analysis for sketches produced by architects. This phase is fundamental and crucial for the whole design and construction process of a building. To give architects a better support, we developed a CAD tool for conceptual design and a knowledge specification tool. The knowledge is specific to one class of buildings and it can be reused. Based on a dynamic and domain-specific knowledge ontology, different types of design rules formalize this knowledge in a graph-based form. An expressive visual language provides a user-friendly, human readable representation. Finally, a consistency analysis tool enables conceptual designs to be checked against this formal conceptual knowledge. In this article, we concentrate on the knowledge specification part. For that, we introduce the concepts and usage of a novel visual language and describe its semantics. To demonstrate the usability of our approach, two graph-based visual tools for knowledge specification and conceptual design are explained. KW - CAD KW - CAD KW - Bauingenieurwesen KW - CAD KW - civil engineering Y1 - 2007 ER -