[{"type":"journal_article","publication":"Communications of the Association for Information Systems","status":"public","user_id":"16205","department":[{"_id":"276"},{"_id":"526"},{"_id":"196"}],"project":[{"_id":"160","name":"DatenraumKultur: Use Case 1 - Kulturplattformen - Datenraum Kultur"}],"_id":"65105","language":[{"iso":"eng"}],"publication_status":"accepted","citation":{"ama":"zur Heiden P, Halimeh H, Hansmeier P, et al. Data Spaces for Heterogeneous Data Ecosystems – Findings from a Design Study in the Cultural Sector. <i>Communications of the Association for Information Systems</i>.","chicago":"Heiden, Philipp zur, Haya Halimeh, Philipp Hansmeier, Christian Vorbohle, Maike Althaus, Daniel Beverungen, Dennis Kundisch, and Oliver Müller. “Data Spaces for Heterogeneous Data Ecosystems – Findings from a Design Study in the Cultural Sector.” <i>Communications of the Association for Information Systems</i>, n.d.","ieee":"P. zur Heiden <i>et al.</i>, “Data Spaces for Heterogeneous Data Ecosystems – Findings from a Design Study in the Cultural Sector,” <i>Communications of the Association for Information Systems</i>.","apa":"zur Heiden, P., Halimeh, H., Hansmeier, P., Vorbohle, C., Althaus, M., Beverungen, D., Kundisch, D., &#38; Müller, O. (n.d.). Data Spaces for Heterogeneous Data Ecosystems – Findings from a Design Study in the Cultural Sector. <i>Communications of the Association for Information Systems</i>.","bibtex":"@article{zur Heiden_Halimeh_Hansmeier_Vorbohle_Althaus_Beverungen_Kundisch_Müller, title={Data Spaces for Heterogeneous Data Ecosystems – Findings from a Design Study in the Cultural Sector}, journal={Communications of the Association for Information Systems}, author={zur Heiden, Philipp and Halimeh, Haya and Hansmeier, Philipp and Vorbohle, Christian and Althaus, Maike and Beverungen, Daniel and Kundisch, Dennis and Müller, Oliver} }","short":"P. zur Heiden, H. Halimeh, P. Hansmeier, C. Vorbohle, M. Althaus, D. Beverungen, D. Kundisch, O. Müller, Communications of the Association for Information Systems (n.d.).","mla":"zur Heiden, Philipp, et al. “Data Spaces for Heterogeneous Data Ecosystems – Findings from a Design Study in the Cultural Sector.” <i>Communications of the Association for Information Systems</i>."},"year":"2026","author":[{"full_name":"zur Heiden, Philipp","id":"64394","last_name":"zur Heiden","first_name":"Philipp"},{"last_name":"Halimeh","full_name":"Halimeh, Haya","id":"87673","first_name":"Haya"},{"last_name":"Hansmeier","full_name":"Hansmeier, Philipp","id":"55603","first_name":"Philipp"},{"first_name":"Christian","last_name":"Vorbohle","full_name":"Vorbohle, Christian","id":"29951"},{"last_name":"Althaus","full_name":"Althaus, Maike","id":"61896","first_name":"Maike"},{"last_name":"Beverungen","full_name":"Beverungen, Daniel","id":"59677","first_name":"Daniel"},{"first_name":"Dennis","last_name":"Kundisch","id":"21117","full_name":"Kundisch, Dennis"},{"first_name":"Oliver","id":"72849","full_name":"Müller, Oliver","last_name":"Müller"}],"date_created":"2026-03-24T13:31:24Z","date_updated":"2026-03-27T08:24:49Z","title":"Data Spaces for Heterogeneous Data Ecosystems – Findings from a Design Study in the Cultural Sector"},{"publication":"International Conference on Information Systems Development","type":"conference","abstract":[{"lang":"eng","text":"Recommendation systems are essential for delivering personalized content across e-commerce and streaming services. However, traditional methods often fail in cold-start scenarios where new items lack prior interactions. Recent advances in large language models (LLMs) offer a promising alternative. In this paper, we adopt the retrieve-and-recommend framework and propose to fine-tune the LLM jointly on warm-and cold-start next-item recommendation tasks, thus, mitigating the need for separate models for both item types. We computationally compare zero-shot prompting, in-context learning, and fine-tuning using the same LLM backbone, and benchmark them against strong PLM-based baselines. Our findings provide practical insights into the trade-offs between accuracy and computational cost of these methods for next-item recommendation. To enhance reproducibility, we release the source code under https://github. com/HayaHalimeh/LLMs-For-Next-Item-Recommendation.git."}],"status":"public","_id":"63524","department":[{"_id":"195"},{"_id":"196"}],"user_id":"87673","language":[{"iso":"eng"}],"publication_identifier":{"issn":["2938-5202"]},"publication_status":"published","year":"2025","citation":{"apa":"Halimeh, H., Freese, F., &#38; Müller, O. (2025). LLMs For Warm and Cold Next-Item Recommendation: A Comparative Study across Zero-Shot Prompting, In-Context Learning and Fine-Tuning. <i>International Conference on Information Systems Development</i>. <a href=\"https://doi.org/10.62036/isd.2025.68\">https://doi.org/10.62036/isd.2025.68</a>","bibtex":"@inproceedings{Halimeh_Freese_Müller_2025, title={LLMs For Warm and Cold Next-Item Recommendation: A Comparative Study across Zero-Shot Prompting, In-Context Learning and Fine-Tuning}, DOI={<a href=\"https://doi.org/10.62036/isd.2025.68\">10.62036/isd.2025.68</a>}, booktitle={International Conference on Information Systems Development}, publisher={University of Gdansk, Department of Business Informatics &#38; University of Belgrade, Faculty of Organizational Sciences}, author={Halimeh, Haya and Freese, Florian and Müller, Oliver}, year={2025} }","short":"H. Halimeh, F. Freese, O. Müller, in: International Conference on Information Systems Development, University of Gdansk, Department of Business Informatics &#38; University of Belgrade, Faculty of Organizational Sciences, 2025.","mla":"Halimeh, Haya, et al. “LLMs For Warm and Cold Next-Item Recommendation: A Comparative Study across Zero-Shot Prompting, In-Context Learning and Fine-Tuning.” <i>International Conference on Information Systems Development</i>, University of Gdansk, Department of Business Informatics &#38; University of Belgrade, Faculty of Organizational Sciences, 2025, doi:<a href=\"https://doi.org/10.62036/isd.2025.68\">10.62036/isd.2025.68</a>.","ama":"Halimeh H, Freese F, Müller O. LLMs For Warm and Cold Next-Item Recommendation: A Comparative Study across Zero-Shot Prompting, In-Context Learning and Fine-Tuning. In: <i>International Conference on Information Systems Development</i>. University of Gdansk, Department of Business Informatics &#38; University of Belgrade, Faculty of Organizational Sciences; 2025. doi:<a href=\"https://doi.org/10.62036/isd.2025.68\">10.62036/isd.2025.68</a>","chicago":"Halimeh, Haya, Florian Freese, and Oliver Müller. “LLMs For Warm and Cold Next-Item Recommendation: A Comparative Study across Zero-Shot Prompting, In-Context Learning and Fine-Tuning.” In <i>International Conference on Information Systems Development</i>. University of Gdansk, Department of Business Informatics &#38; University of Belgrade, Faculty of Organizational Sciences, 2025. <a href=\"https://doi.org/10.62036/isd.2025.68\">https://doi.org/10.62036/isd.2025.68</a>.","ieee":"H. Halimeh, F. Freese, and O. Müller, “LLMs For Warm and Cold Next-Item Recommendation: A Comparative Study across Zero-Shot Prompting, In-Context Learning and Fine-Tuning,” 2025, doi: <a href=\"https://doi.org/10.62036/isd.2025.68\">10.62036/isd.2025.68</a>."},"oa":"1","publisher":"University of Gdansk, Department of Business Informatics & University of Belgrade, Faculty of Organizational Sciences","date_updated":"2026-01-07T13:47:43Z","author":[{"first_name":"Haya","full_name":"Halimeh, Haya","id":"87673","last_name":"Halimeh"},{"full_name":"Freese, Florian","last_name":"Freese","first_name":"Florian"},{"last_name":"Müller","full_name":"Müller, Oliver","first_name":"Oliver"}],"date_created":"2026-01-07T13:36:53Z","title":"LLMs For Warm and Cold Next-Item Recommendation: A Comparative Study across Zero-Shot Prompting, In-Context Learning and Fine-Tuning","doi":"10.62036/isd.2025.68","main_file_link":[{"open_access":"1"}]},{"status":"public","abstract":[{"lang":"eng","text":"Data spaces have become a strategic pillar of Europe's digital agenda, enabling sovereign, legally compliant data sharing within decentralized ecosystems. As data space initiatives evolve, personalized recommendations are increasingly recognized as key use cases. However, traditional recommendation approaches typically rely on centralized aggregation of user behavior data-directly conflicting with the core ethos of data spaces: sovereignty, privacy, and trust. Federated recommendation systems offer a promising alternative by training models locally and exchanging only intermediate parameters to build a global model. Despite this potential, the integration of federated recommendation techniques and data space architectures remains largely underexplored in research and practice. This paper addresses this gap by designing and evaluating a prototype of a federated recommendation system specifically tailored for data spaces and compliant with their underlying infrastructure. Our findings highlight the viability of developing privacy-preserving, collaborative recommendation systems within data spaces, and contribute to the broader adoption of AI across these emerging ecosystems."}],"type":"conference","publication":"2025 27th International Conference on Business Informatics (CBI)","language":[{"iso":"eng"}],"user_id":"87673","department":[{"_id":"195"},{"_id":"196"}],"_id":"63523","citation":{"ieee":"H. Halimeh and P. zur Heiden, “Preserving Sovereignty and Privacy for Personalization: Designing a Federated Recommendation System for Data Spaces,” 2025, doi: <a href=\"https://doi.org/10.1109/cbi68102.2025.00019\">10.1109/cbi68102.2025.00019</a>.","chicago":"Halimeh, Haya, and Philipp zur Heiden. “Preserving Sovereignty and Privacy for Personalization: Designing a Federated Recommendation System for Data Spaces.” In <i>2025 27th International Conference on Business Informatics (CBI)</i>. IEEE, 2025. <a href=\"https://doi.org/10.1109/cbi68102.2025.00019\">https://doi.org/10.1109/cbi68102.2025.00019</a>.","ama":"Halimeh H, zur Heiden P. Preserving Sovereignty and Privacy for Personalization: Designing a Federated Recommendation System for Data Spaces. In: <i>2025 27th International Conference on Business Informatics (CBI)</i>. IEEE; 2025. doi:<a href=\"https://doi.org/10.1109/cbi68102.2025.00019\">10.1109/cbi68102.2025.00019</a>","apa":"Halimeh, H., &#38; zur Heiden, P. (2025). Preserving Sovereignty and Privacy for Personalization: Designing a Federated Recommendation System for Data Spaces. <i>2025 27th International Conference on Business Informatics (CBI)</i>. <a href=\"https://doi.org/10.1109/cbi68102.2025.00019\">https://doi.org/10.1109/cbi68102.2025.00019</a>","mla":"Halimeh, Haya, and Philipp zur Heiden. “Preserving Sovereignty and Privacy for Personalization: Designing a Federated Recommendation System for Data Spaces.” <i>2025 27th International Conference on Business Informatics (CBI)</i>, IEEE, 2025, doi:<a href=\"https://doi.org/10.1109/cbi68102.2025.00019\">10.1109/cbi68102.2025.00019</a>.","short":"H. Halimeh, P. zur Heiden, in: 2025 27th International Conference on Business Informatics (CBI), IEEE, 2025.","bibtex":"@inproceedings{Halimeh_zur Heiden_2025, title={Preserving Sovereignty and Privacy for Personalization: Designing a Federated Recommendation System for Data Spaces}, DOI={<a href=\"https://doi.org/10.1109/cbi68102.2025.00019\">10.1109/cbi68102.2025.00019</a>}, booktitle={2025 27th International Conference on Business Informatics (CBI)}, publisher={IEEE}, author={Halimeh, Haya and zur Heiden, Philipp}, year={2025} }"},"year":"2025","publication_status":"published","main_file_link":[{"open_access":"1"}],"doi":"10.1109/cbi68102.2025.00019","title":"Preserving Sovereignty and Privacy for Personalization: Designing a Federated Recommendation System for Data Spaces","date_created":"2026-01-07T13:34:02Z","author":[{"last_name":"Halimeh","id":"87673","full_name":"Halimeh, Haya","first_name":"Haya"},{"first_name":"Philipp","id":"64394","full_name":"zur Heiden, Philipp","last_name":"zur Heiden"}],"date_updated":"2026-01-07T13:49:45Z","oa":"1","publisher":"IEEE"},{"type":"conference","status":"public","abstract":[{"lang":"eng","text":"Recommender systems (RS) can support sustainable development by steering users toward more sustainable choices. Sustainability-aware explanations represent one avenue for contributing to this goal by foregrounding the environmental and social aspects of the recommended products or services. This paper advances the line of research on sustainability-aware explanations by integrating nudging mechanisms into their design and by evaluating their effectiveness through a randomized between-subjects online vignette experiment across two item domains (). Our findings offer actionable design guidelines for building RS that foster sustainability-aware decision making and enrich the empirical foundation for impact-oriented research on explanation in RS.\r\n"}],"department":[{"_id":"195"},{"_id":"196"}],"user_id":"87673","_id":"63525","language":[{"iso":"eng"}],"citation":{"ieee":"H. Halimeh and O. Müller, “Towards Greener Choices: Decision Information Nudging for Sustainability-Aware Recommender Explanations,” presented at the  The Second International Workshop on Recommender Systems for Sustainability and Social Good, RecSoGood 2025, Prague, Czech Republic, 2025, doi: <a href=\"https://doi.org/10.1007/978-3-032-13342-7\">10.1007/978-3-032-13342-7</a>.","chicago":"Halimeh, Haya, and Oliver Müller. “Towards Greener Choices: Decision Information Nudging for Sustainability-Aware Recommender Explanations,” 2025. <a href=\"https://doi.org/10.1007/978-3-032-13342-7\">https://doi.org/10.1007/978-3-032-13342-7</a>.","ama":"Halimeh H, Müller O. Towards Greener Choices: Decision Information Nudging for Sustainability-Aware Recommender Explanations. In: ; 2025. doi:<a href=\"https://doi.org/10.1007/978-3-032-13342-7\">10.1007/978-3-032-13342-7</a>","apa":"Halimeh, H., &#38; Müller, O. (2025). <i>Towards Greener Choices: Decision Information Nudging for Sustainability-Aware Recommender Explanations</i>.  The Second International Workshop on Recommender Systems for Sustainability and Social Good, RecSoGood 2025, Prague, Czech Republic. <a href=\"https://doi.org/10.1007/978-3-032-13342-7\">https://doi.org/10.1007/978-3-032-13342-7</a>","short":"H. Halimeh, O. Müller, in: 2025.","bibtex":"@inproceedings{Halimeh_Müller_2025, title={Towards Greener Choices: Decision Information Nudging for Sustainability-Aware Recommender Explanations}, DOI={<a href=\"https://doi.org/10.1007/978-3-032-13342-7\">10.1007/978-3-032-13342-7</a>}, author={Halimeh, Haya and Müller, Oliver}, year={2025} }","mla":"Halimeh, Haya, and Oliver Müller. <i>Towards Greener Choices: Decision Information Nudging for Sustainability-Aware Recommender Explanations</i>. 2025, doi:<a href=\"https://doi.org/10.1007/978-3-032-13342-7\">10.1007/978-3-032-13342-7</a>."},"year":"2025","author":[{"full_name":"Halimeh, Haya","id":"87673","last_name":"Halimeh","first_name":"Haya"},{"first_name":"Oliver","id":"72849","full_name":"Müller, Oliver","last_name":"Müller"}],"date_created":"2026-01-07T13:40:05Z","date_updated":"2026-01-07T13:46:50Z","oa":"1","conference":{"location":"Prague, Czech Republic","start_date":"2025-09-26","name":" The Second International Workshop on Recommender Systems for Sustainability and Social Good, RecSoGood 2025"},"doi":"10.1007/978-3-032-13342-7","main_file_link":[{"open_access":"1","url":"https://link.springer.com/book/10.1007/978-3-032-13342-7"}],"title":"Towards Greener Choices: Decision Information Nudging for Sustainability-Aware Recommender Explanations"},{"department":[{"_id":"276"},{"_id":"526"},{"_id":"196"},{"_id":"735"}],"user_id":"87673","_id":"63026","project":[{"_id":"160","name":"DatenraumKultur: Use Case 1 - Kulturplattformen - Datenraum Kultur"}],"language":[{"iso":"ger"}],"type":"working_paper","status":"public","author":[{"first_name":"Maike","last_name":"Althaus","id":"61896","full_name":"Althaus, Maike"},{"last_name":"Beverungen","id":"59677","full_name":"Beverungen, Daniel","first_name":"Daniel"},{"full_name":"Flath, Beate","id":"58896","last_name":"Flath","orcid":"https://orcid.org/0000-0002-1648-0796","first_name":"Beate"},{"first_name":"Haya","last_name":"Halimeh","full_name":"Halimeh, Haya","id":"87673"},{"first_name":"Philipp","id":"55603","full_name":"Hansmeier, Philipp","last_name":"Hansmeier"},{"last_name":"zur Heiden","id":"64394","full_name":"zur Heiden, Philipp","first_name":"Philipp"},{"last_name":"Kundisch","id":"21117","full_name":"Kundisch, Dennis","first_name":"Dennis"},{"first_name":"Michelle","last_name":"Müller","id":"50286","full_name":"Müller, Michelle"},{"last_name":"Müller","id":"72849","full_name":"Müller, Oliver","first_name":"Oliver"},{"first_name":"Simon","last_name":"Oberthür","full_name":"Oberthür, Simon","id":"383"},{"id":"29951","full_name":"Vorbohle, Christian","last_name":"Vorbohle","first_name":"Christian"},{"first_name":"Maryam","last_name":"Momen Pour Tafreshi","full_name":"Momen Pour Tafreshi, Maryam"},{"first_name":"Sebastian","last_name":"Mauß","full_name":"Mauß, Sebastian"},{"last_name":"Mücke","full_name":"Mücke, Alina","first_name":"Alina"},{"first_name":"Jörg","last_name":"Müller","full_name":"Müller, Jörg"},{"first_name":"Malte","last_name":"Peter","full_name":"Peter, Malte"},{"full_name":"Schmitt-Chandon, Ariane","last_name":"Schmitt-Chandon","first_name":"Ariane"},{"first_name":"Kerstin","last_name":"Sellerberg","full_name":"Sellerberg, Kerstin"},{"full_name":"Steinhäuser, Moritz","last_name":"Steinhäuser","first_name":"Moritz"}],"date_created":"2025-12-10T15:50:35Z","date_updated":"2026-01-07T13:41:32Z","title":"Positionspapier Use Case 1: Vernetzte Kulturplattformen","publication_status":"published","citation":{"ieee":"M. Althaus <i>et al.</i>, <i>Positionspapier Use Case 1: Vernetzte Kulturplattformen</i>. Universität Paderborn, SICP, 2025.","chicago":"Althaus, Maike, Daniel Beverungen, Beate Flath, Haya Halimeh, Philipp Hansmeier, Philipp zur Heiden, Dennis Kundisch, et al. <i>Positionspapier Use Case 1: Vernetzte Kulturplattformen</i>. Universität Paderborn, SICP, 2025.","ama":"Althaus M, Beverungen D, Flath B, et al. <i>Positionspapier Use Case 1: Vernetzte Kulturplattformen</i>.; 2025.","apa":"Althaus, M., Beverungen, D., Flath, B., Halimeh, H., Hansmeier, P., zur Heiden, P., Kundisch, D., Müller, M., Müller, O., Oberthür, S., Vorbohle, C., Momen Pour Tafreshi, M., Mauß, S., Mücke, A., Müller, J., Peter, M., Schmitt-Chandon, A., Sellerberg, K., &#38; Steinhäuser, M. (2025). <i>Positionspapier Use Case 1: Vernetzte Kulturplattformen</i>.","bibtex":"@book{Althaus_Beverungen_Flath_Halimeh_Hansmeier_zur Heiden_Kundisch_Müller_Müller_Oberthür_et al._2025, place={Universität Paderborn, SICP}, title={Positionspapier Use Case 1: Vernetzte Kulturplattformen}, author={Althaus, Maike and Beverungen, Daniel and Flath, Beate and Halimeh, Haya and Hansmeier, Philipp and zur Heiden, Philipp and Kundisch, Dennis and Müller, Michelle and Müller, Oliver and Oberthür, Simon and et al.}, year={2025} }","mla":"Althaus, Maike, et al. <i>Positionspapier Use Case 1: Vernetzte Kulturplattformen</i>. 2025.","short":"M. Althaus, D. Beverungen, B. Flath, H. Halimeh, P. Hansmeier, P. zur Heiden, D. Kundisch, M. Müller, O. Müller, S. Oberthür, C. Vorbohle, M. Momen Pour Tafreshi, S. Mauß, A. Mücke, J. Müller, M. Peter, A. Schmitt-Chandon, K. Sellerberg, M. Steinhäuser, Positionspapier Use Case 1: Vernetzte Kulturplattformen, Universität Paderborn, SICP, 2025."},"place":"Universität Paderborn, SICP","year":"2025"},{"user_id":"87673","department":[{"_id":"195"},{"_id":"196"}],"_id":"50431","language":[{"iso":"eng"}],"type":"conference","publication":"Workshop on Recommenders in Tourism, co-located with the 17th ACM Conference on Recommender Systems","status":"public","abstract":[{"text":"Recommender systems now span the entire customer journey. Amid the multitude of diversified experi- ences, immersing in cultural events has become a key aspect of tourism. Cultural events, however, suffer from fleeting lifecycles, evade exact replication, and invariably lie in the future. In addition, their low standardization makes harnessing historical data regarding event content or past patron evaluations intricate. The distinctive traits of events thereby compound the challenge of the cold-start dilemma in event recommenders. Content-based recommendations stand as a viable avenue to alleviate this issue, functioning even in scenarios where item-user information is scarce. Still, the effectiveness of content- based recommendations often hinges on the quality of the data representation they build upon. In this study, we explore an array of cutting-edge uni- and multimodal vision and language foundation models (VL-FMs) for this purpose. Next, we derive content-based recommendations through a straightforward clustering approach that groups akin events together, and evaluate the efficacy of the models through a series of online user experiments across three dimensions: similarity-based evaluation, comparison-based evaluation, and clustering assignment evaluation. Our experiments generated four major findings. First, we found that all VL-FMs consistently outperformed a naive baseline of recommending randomly drawn events. Second, unimodal text-based embeddings were surprisingly on par or in some cases even superior to multimodal embeddings. Third, multimodal embeddings yielded arguably more fine-grained and diverse clusters in comparison to their unimodal counterparts. Finally, we could confirm that cross event interest is indeed reliant on the perceived similarity of events, resonating with the notion of similarity in content-based recommendations. All in all, we believe that leveraging the potential of contemporary FMs for content-based event recommendations would help address the cold-start problem and propel this field of research forward in new and exciting ways.","lang":"eng"}],"date_created":"2024-01-10T14:20:12Z","author":[{"first_name":"Haya","last_name":"Halimeh","full_name":"Halimeh, Haya","id":"87673"},{"full_name":"Freese, Florian","last_name":"Freese","first_name":"Florian"},{"first_name":"Oliver","last_name":"Müller","id":"72849","full_name":"Müller, Oliver"}],"oa":"1","date_updated":"2024-01-10T16:10:04Z","main_file_link":[{"open_access":"1","url":"https://scholar.google.com/citations?view_op=view_citation&hl=en&user=zBlrdP4AAAAJ&citation_for_view=zBlrdP4AAAAJ:UeHWp8X0CEIC"}],"conference":{"start_date":"2023-09-18","name":"Workshop on Recommenders in Tourism, co-located with the 17th ACM Conference on Recommender Systems","end_date":"2023-09-22"},"title":"Event Recommendations through the Lens of Vision and Language Foundation Models","citation":{"mla":"Halimeh, Haya, et al. “Event Recommendations through the Lens of Vision and Language Foundation Models.” <i>Workshop on Recommenders in Tourism, Co-Located with the 17th ACM Conference on Recommender Systems</i>, 2023.","bibtex":"@inproceedings{Halimeh_Freese_Müller_2023, title={Event Recommendations through the Lens of Vision and Language Foundation Models}, booktitle={Workshop on Recommenders in Tourism, co-located with the 17th ACM Conference on Recommender Systems}, author={Halimeh, Haya and Freese, Florian and Müller, Oliver}, year={2023} }","short":"H. Halimeh, F. Freese, O. Müller, in: Workshop on Recommenders in Tourism, Co-Located with the 17th ACM Conference on Recommender Systems, 2023.","apa":"Halimeh, H., Freese, F., &#38; Müller, O. (2023). Event Recommendations through the Lens of Vision and Language Foundation Models. <i>Workshop on Recommenders in Tourism, Co-Located with the 17th ACM Conference on Recommender Systems</i>. Workshop on Recommenders in Tourism, co-located with the 17th ACM Conference on Recommender Systems.","ieee":"H. Halimeh, F. Freese, and O. Müller, “Event Recommendations through the Lens of Vision and Language Foundation Models,” presented at the Workshop on Recommenders in Tourism, co-located with the 17th ACM Conference on Recommender Systems, 2023.","chicago":"Halimeh, Haya, Florian Freese, and Oliver Müller. “Event Recommendations through the Lens of Vision and Language Foundation Models.” In <i>Workshop on Recommenders in Tourism, Co-Located with the 17th ACM Conference on Recommender Systems</i>, 2023.","ama":"Halimeh H, Freese F, Müller O. Event Recommendations through the Lens of Vision and Language Foundation Models. In: <i>Workshop on Recommenders in Tourism, Co-Located with the 17th ACM Conference on Recommender Systems</i>. ; 2023."},"year":"2023"},{"abstract":[{"text":"Clinical depression is a serious mental disorder that poses challenges for both personal and public health. Millions of people struggle with depression each year, but for many, the disorder goes undiagnosed or untreated. Over the last decade, early depression detection on social media emerged as an interdisciplinary research field. However, there is still a gap in detecting hesitant, depression-susceptible individuals with minimal direct depressive signals at an early stage. We, therefore, take up this open point and leverage posts from Reddit to fill the addressed gap. Our results demonstrate the potential of contemporary Transformer architectures in yielding promising predictive capabilities for mental health research. Furthermore, we investigate the model’s interpretability using a surrogate and a topic modeling approach. Based on our findings, we consider this work as a further step towards developing a better understanding of mental eHealth and hope that our results can support the development of future technologies.","lang":"eng"}],"status":"public","publication":"Hawaii International Conference on System Sciences","type":"conference","keyword":["Social Media and Healthcare Technology","early depression detection","liwc","mental health","transfer learning","transformer architectures"],"language":[{"iso":"eng"}],"_id":"45270","department":[{"_id":"195"},{"_id":"196"}],"user_id":"60721","year":"2023","citation":{"ama":"Halimeh H, Caron M, Müller O. Early Depression Detection with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based Features. In: <i>Hawaii International Conference on System Sciences</i>. ; 2023.","chicago":"Halimeh, Haya, Matthew Caron, and Oliver Müller. “Early Depression Detection with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based Features.” In <i>Hawaii International Conference on System Sciences</i>, 2023.","ieee":"H. Halimeh, M. Caron, and O. Müller, “Early Depression Detection with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based Features,” presented at the Hawaii International Conference on System Sciences, 2023.","mla":"Halimeh, Haya, et al. “Early Depression Detection with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based Features.” <i>Hawaii International Conference on System Sciences</i>, 2023.","bibtex":"@inproceedings{Halimeh_Caron_Müller_2023, title={Early Depression Detection with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based Features}, booktitle={Hawaii International Conference on System Sciences}, author={Halimeh, Haya and Caron, Matthew and Müller, Oliver}, year={2023} }","short":"H. Halimeh, M. Caron, O. Müller, in: Hawaii International Conference on System Sciences, 2023.","apa":"Halimeh, H., Caron, M., &#38; Müller, O. (2023). Early Depression Detection with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based Features. <i>Hawaii International Conference on System Sciences</i>. Hawaii International Conference on System Sciences."},"publication_status":"published","related_material":{"link":[{"url":"https://hdl.handle.net/10125/103046","relation":"confirmation"}]},"title":"Early Depression Detection with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based Features","conference":{"end_date":"2023-01-06","name":"Hawaii International Conference on System Sciences","start_date":"2023-01-03"},"main_file_link":[{"url":"https://scholarspace.manoa.hawaii.edu/items/2ddab486-5d2f-4302-8de3-a8b24017da3d","open_access":"1"}],"date_updated":"2024-01-10T15:16:37Z","oa":"1","author":[{"id":"87673","full_name":"Halimeh, Haya","last_name":"Halimeh","first_name":"Haya"},{"first_name":"Matthew","last_name":"Caron","id":"60721","full_name":"Caron, Matthew"},{"first_name":"Oliver","last_name":"Müller","full_name":"Müller, Oliver","id":"72849"}],"date_created":"2023-05-25T10:25:21Z"}]