@inproceedings{45188,
  author       = {{Werthmann, Julian and Scheideler, Christian and Coy, Sam and Czumaj, Artur and Schneider, Philipp}},
  title        = {{{Routing Schemes for Hybrid Communication Networks}}},
  doi          = {{10.48550/ARXIV.2210.05333}},
  year         = {{2023}},
}

@inproceedings{44855,
  abstract     = {{Market transactions are subject to information asymmetry about the delivered value proposition, causing transaction costs and adverse market effects among buyers and sellers. Information systems research has investigated how review systems can reduce information asymmetry in business-to-consumer markets. However, these systems cannot be readily applied to business-to-business markets, are vulnerable to manipulation, and suffer from conceptual weak spots since they use textual data or star ratings. Building on design science research, we conceptualize a new class of reputation systems based on monetary-based payments as quantitative ratings for each transaction stored on a blockchain. Using cryptography, we show that our system assures content confidentiality so that buyers can share and sell their ratings selectively, establishing a reputation ecosystem. Our prescriptive insights advance the design of reputation systems and offer new paths to understanding the antecedents, dynamics, and consequences to reduce information asymmetry in B2B transactions.}},
  author       = {{Hemmrich, Simon and Bobolz, Jan and Beverungen, Daniel and Blömer, Johannes}},
  booktitle    = {{ECIS 2023 Research Papers}},
  title        = {{{Designing Business Reputation Ecosystems — A Method for Issuing and Trading Monetary Ratings on a Blockchain}}},
  year         = {{2023}},
}

@misc{45243,
  author       = {{N., N.}},
  title        = {{{Development and Evaluation of a Model-Based UI Prototyping Experimentation Approach}}},
  year         = {{2023}},
}

@inproceedings{45312,
  author       = {{Karakaya, Kadiray and Bodden, Eric}},
  booktitle    = {{2023 IEEE Conference on Software Testing, Verification and Validation (ICST)}},
  publisher    = {{IEEE}},
  title        = {{{Two Sparsification Strategies for Accelerating Demand-Driven Pointer Analysis}}},
  doi          = {{10.1109/icst57152.2023.00036}},
  year         = {{2023}},
}

@misc{43375,
  author       = {{Koch, Angelina}},
  title        = {{{Privacy-Preserving Collection and Evaluation of Log Files}}},
  year         = {{2023}},
}

@article{45484,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>Graffiti is an urban phenomenon that is increasingly attracting the interest of the sciences. To the best of our knowledge, no suitable data corpora are available for systematic research until now. The Information System Graffiti in Germany project (<jats:sc>Ingrid</jats:sc>) closes this gap by dealing with graffiti image collections that have been made available to the project for public use. Within <jats:sc>Ingrid</jats:sc>, the graffiti images are collected, digitized and annotated. With this work, we aim to support the rapid access to a comprehensive data source on <jats:sc>Ingrid</jats:sc> targeted especially by researchers. In particular, we present <jats:sc>Ingrid</jats:sc>KG, an RDF knowledge graph of annotated graffiti, abides by the Linked Data and FAIR principles. We weekly update <jats:sc>Ingrid</jats:sc>KG by augmenting the new annotated graffiti to our knowledge graph. Our generation pipeline applies RDF data conversion, link discovery and data fusion approaches to the original data. The current version of <jats:sc>Ingrid</jats:sc>KG contains 460,640,154 triples and is linked to 3 other knowledge graphs by over 200,000 links. In our use case studies, we demonstrate the usefulness of our knowledge graph for different applications.</jats:p>}},
  author       = {{Sherif, Mohamed Ahmed and da Silva, Ana Alexandra Morim and Pestryakova, Svetlana and Ahmed, Abdullah Fathi and Niemann, Sven and Ngomo, Axel-Cyrille Ngonga}},
  issn         = {{2052-4463}},
  journal      = {{Scientific Data}},
  keywords     = {{Library and Information Sciences, Statistics, Probability and Uncertainty, Computer Science Applications, Education, Information Systems, Statistics and Probability}},
  number       = {{1}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{IngridKG: A FAIR Knowledge Graph of Graffiti}}},
  doi          = {{10.1038/s41597-023-02199-8}},
  volume       = {{10}},
  year         = {{2023}},
}

@phdthesis{45580,
  author       = {{Castenow, Jannik}},
  title        = {{{Local Protocols for Contracting and Expanding Robot Formation Problems}}},
  doi          = {{10.17619/UNIPB/1-1750}},
  year         = {{2023}},
}

@phdthesis{45579,
  author       = {{Knollmann, Till}},
  title        = {{{Online Algorithms for Allocating Heterogeneous Resources}}},
  doi          = {{10.17619/UNIPB/1-1751}},
  year         = {{2023}},
}

@inproceedings{45695,
  author       = {{Hotegni, Sedjro Salomon and Mahabadi, Sepideh and Vakilian, Ali}},
  booktitle    = {{Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, USA. PMLR 202, 2023.}},
  keywords     = {{Fair range clustering}},
  location     = {{Honolulu, Hawaii, USA}},
  title        = {{{Approximation Algorithms for Fair Range Clustering}}},
  year         = {{2023}},
}

@inproceedings{43060,
  author       = {{Hebrok, Sven Niclas and Nachtigall, Simon and Maehren, Marcel and Erinola, Nurullah and Merget, Robert and Somorovsky, Juraj and Schwenk, Jörg}},
  booktitle    = {{32nd USENIX Security Symposium}},
  title        = {{{We Really Need to Talk About Session Tickets: A Large-Scale Analysis of Cryptographic Dangers with TLS Session Tickets}}},
  year         = {{2023}},
}

@inproceedings{45793,
  abstract     = {{The global megatrends of digitization and sustainability lead to new challenges for the design and management of technical products in industrial companies. Product management - as the bridge between market and company - has the task to absorb and combine the manifold requirements and make the right product-related decisions. In the process, product management is confronted with heterogeneous information, rapidly changing portfolio components, as well as increasing product, and organizational complexity. Combining and utilizing data from different sources, e.g., product usage data and social media data leads to promising potentials to improve the quality of product-related decisions. In this paper, we reinforce the need for data-driven product management as an interdisciplinary field of action. The state of data-driven product management in practice was analyzed by conducting workshops with six manufacturing companies and hosting a focus group meeting with experts from different industries. We investigate the expectations and derive requirements leading us to open research questions, a vision for data-driven product management, and a research agenda to shape future research efforts.}},
  author       = {{Grigoryan, Khoren and Fichtler, Timm and Schreiner, Nick and Rabe, Martin and Panzner, Melina and Kühn, Arno and Dumitrescu, Roman and Koldewey, Christian}},
  booktitle    = {{Procedia CIRP 33}},
  keywords     = {{Product Management, Data Analytics, Data-Driven Design, Product-related data, Lifecycle Data, Tool-support}},
  location     = {{Sydney}},
  title        = {{{Data-Driven Product Management: A Practitioner-Driven Research Agenda}}},
  year         = {{2023}},
}

@inproceedings{45812,
  author       = {{Özcan, Leon and Fichtler, Timm and Kasten, Benjamin and Koldewey, Christian and Dumitrescu, Roman}},
  keywords     = {{Digital Platform, Platform Strategy, Strategic Management, Platform Life Cycle, Interview Study, Business Model, Business-to-Business, Two-sided Market, Multi-sided Market}},
  location     = {{Ljubljana}},
  title        = {{{Interview Study on Strategy Options for Platform Operation in B2B Markets}}},
  year         = {{2023}},
}

@inproceedings{33734,
  abstract     = {{Many applications require explainable node classification in knowledge graphs. Towards this end, a popular ``white-box'' approach is class expression learning: Given sets of positive and negative nodes, class expressions in description logics are learned that separate positive from negative nodes. Most existing approaches are search-based approaches generating many candidate class expressions and selecting the best one. However, they often take a long time to find suitable class expressions. In this paper, we cast class expression learning as a translation problem and propose a new family of class expression learning approaches which we dub neural class expression synthesizers. Training examples are ``translated'' into class expressions in a fashion akin to machine translation. Consequently, our synthesizers are not subject to the runtime limitations of search-based approaches. We study three instances of this novel family of approaches based on LSTMs, GRUs, and set transformers, respectively. An evaluation of our approach on four benchmark datasets suggests that it can effectively synthesize high-quality class expressions with respect to the input examples in approximately one second on average. Moreover, a comparison to state-of-the-art approaches suggests that we achieve better F-measures on large datasets. For reproducibility purposes, we provide our implementation as well as pretrained models in our public GitHub repository at https://github.com/dice-group/NeuralClassExpressionSynthesis}},
  author       = {{KOUAGOU, N'Dah Jean and Heindorf, Stefan and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}},
  booktitle    = {{The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023)}},
  editor       = {{Pesquita, Catia and Jimenez-Ruiz, Ernesto and McCusker, Jamie and Faria, Daniel and Dragoni, Mauro and Dimou, Anastasia and Troncy, Raphael and Hertling, Sven}},
  keywords     = {{Neural network, Concept learning, Description logics}},
  location     = {{Hersonissos, Crete, Greece}},
  pages        = {{209 -- 226}},
  publisher    = {{Springer International Publishing}},
  title        = {{{Neural Class Expression Synthesis}}},
  doi          = {{https://doi.org/10.1007/978-3-031-33455-9_13}},
  volume       = {{13870}},
  year         = {{2023}},
}

@phdthesis{44323,
  abstract     = {{Reading between the lines has so far been reserved for humans. The present dissertation addresses this research gap using machine learning methods.
Implicit expressions are not comprehensible by computers and cannot be localized in the text. However, many texts arise on interpersonal topics that, unlike commercial evaluation texts, often imply information only by means of longer phrases. Examples are the kindness and the attentiveness of a doctor, which are only paraphrased (“he didn’t even look me in the eye”). The analysis of such data, especially the identification and localization of implicit statements, is a research gap (1). This work uses so-called Aspect-based Sentiment Analysis as a method for this purpose. It remains open how the aspect categories to be extracted can be discovered and thematically delineated based on the data (2). Furthermore, it is not yet explored how a collection of tools should look like, with which implicit phrases can be identified and thus made explicit
(3). Last, it is an open question how to correlate the identified phrases from the text data with other data, including the investigation of the relationship between quantitative scores (e.g., school grades) and the thematically related text (4). Based on these research gaps, the research question is posed as follows: Using text mining methods, how can implicit rating content be properly interpreted and thus made explicit before it is automatically categorized and quantified?
The uniqueness of this dissertation is based on the automated recognition of implicit linguistic statements alongside explicit statements. These are identified in unstructured text data so that features expressed only in the text can later be compared across data sources, even though they were not included in rating categories such as stars or school grades. German-language physician ratings from websites in three countries serve as the sample domain. The solution approach consists of data creation, a pipeline for text processing and analyses based on this. In the data creation, aspect classes are identified and delineated across platforms and marked in text data. This results in six datasets with over 70,000 annotated sentences and detailed guidelines. The models that were created based on the training data extract and categorize the aspects. In addition, the sentiment polarity and the evaluation weight, i. e., the importance of each phrase, are determined. The models, which are combined in a pipeline, are used in a prototype in the form of a web application. The analyses built on the pipeline quantify the rating contents by linking the obtained information with further data, thus allowing new insights.
As a result, a toolbox is provided to identify quantifiable rating content and categories using text mining for a sample domain. This is used to evaluate the approach, which in principle can also be adapted to any other domain.}},
  author       = {{Kersting, Joschka}},
  pages        = {{208}},
  publisher    = {{Universität der Bundeswehr München }},
  title        = {{{Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining}}},
  year         = {{2023}},
}

@inbook{45875,
  author       = {{Götte, Thorsten and Knollmann, Till and Meyer auf der Heide, Friedhelm and Scheideler, Christian and Werthmann, Julian}},
  booktitle    = {{On-The-Fly Computing -- Individualized IT-services in dynamic markets}},
  editor       = {{Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner, Marco and Wachsmuth, Henning and Wehrheim, Heike}},
  pages        = {{1----20}},
  publisher    = {{Heinz Nixdorf Institut, Universität Paderborn}},
  title        = {{{Capabilities and Limitations of Local Strategies in Dynamic Networks}}},
  doi          = {{10.5281/zenodo.8060372}},
  volume       = {{412}},
  year         = {{2023}},
}

@inbook{45895,
  author       = {{Karl, Holger and Maack, Marten and Meyer auf der Heide, Friedhelm and Pukrop, Simon and Redder, Adrian}},
  booktitle    = {{On-The-Fly Computing -- Individualized IT-services in dynamic markets}},
  editor       = {{Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner, Marco and Wachsmuth, Henning and Wehrheim, Heike}},
  pages        = {{183--202}},
  publisher    = {{Heinz Nixdorf Institut, Universität Paderborn}},
  title        = {{{On-The-Fly Compute Centers II: Execution of Composed Services in Configurable Compute Centers}}},
  doi          = {{10.5281/zenodo.8068664}},
  volume       = {{412}},
  year         = {{2023}},
}

@inbook{45901,
  author       = {{Blömer, Johannes and Bobolz, Jan and Eidens, Fabian and Jager, Tibor and Kramer, Paul}},
  booktitle    = {{On-The-Fly Computing -- Individualized IT-services in dynamic markets}},
  editor       = {{Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner, Marco and Wachsmuth, Henning and Wehrheim, Heike}},
  pages        = {{237--246}},
  publisher    = {{Heinz Nixdorf Institut, Universität Paderborn}},
  title        = {{{Practical Cryptograhic Techniques for Secure and Privacy-Preserving Customer Loyalty Systems}}},
  doi          = {{10.5281/zenodo.8068755}},
  volume       = {{412}},
  year         = {{2023}},
}

@inbook{45897,
  author       = {{Gottschalk, Sebastian and Vorbohle, Christian and Kundisch, Dennis and Engels, Gregor and Wünderlich, Nacy V.}},
  booktitle    = {{On-The-Fly Computing -- Individualized IT-services in dynamic markets}},
  editor       = {{Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner, Marco and Wachsmuth, Henning and Wehrheim, Heike}},
  pages        = {{203--224}},
  publisher    = {{Heinz Nixdorf Institut, Universität Paderborn}},
  title        = {{{Architectural Management of OTF Computing Markets}}},
  doi          = {{10.5281/zenodo.8068691}},
  volume       = {{412}},
  year         = {{2023}},
}

@inbook{45891,
  author       = {{Blömer, Johannes and Eidens, Fabian and Jager, Tibor and Niehues, David and Scheideler, Christian}},
  booktitle    = {{On-The-Fly Computing -- Individualized IT-services in dynamic markets}},
  editor       = {{Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner, Marco and Wachsmuth, Henning and Wehrheim, Heike}},
  pages        = {{145--164}},
  publisher    = {{Heinz Nixdorf Institut, Universität Paderborn}},
  title        = {{{Robustness and Security}}},
  doi          = {{10.5281/zenodo.8068629}},
  volume       = {{412}},
  year         = {{2023}},
}

@inbook{45882,
  author       = {{Bäumer, Frederik Simon and Chen, Wei-Fan and Geierhos, Michaela and Kersting, Joschka and Wachsmuth, Henning}},
  booktitle    = {{On-The-Fly Computing -- Individualized IT-services in dynamic markets}},
  editor       = {{Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner, Marco and Wachsmuth, Henning and Wehrheim, Heike}},
  pages        = {{65--84}},
  publisher    = {{Heinz Nixdorf Institut, Universität Paderborn}},
  title        = {{{Dialogue-based Requirement Compensation and Style-adjusted Data-to-text Generation}}},
  doi          = {{10.5281/zenodo.8068456}},
  volume       = {{412}},
  year         = {{2023}},
}