Publikationen
178 Übereinstimmungen gefunden / 1-15 16-30 31-45 46-60 61-75 76-90 91-105 106-120 121-135 136-150 151-165 166-178
Mustervertrag Datenaufnahme KonsortSWD (Version 2.0.0).Schallaböck, J., Kreutzer, T., Hoffstätter, U., & Buck, D. (2023).Mustervertrag Datenaufnahme KonsortSWD (Version 2.0.0). Hannover: DZHW. https://doi.org/10.5281/zenodo.10406480 |
Mustervertrag Datennutzung KonsortSWD (Version 3.0.0).Schallaböck, J., Hoffstätter, U., Buck, D., & Linne, M. (2023).Mustervertrag Datennutzung KonsortSWD (Version 3.0.0). Hannover: DZHW. https://doi.org/10.5281/zenodo.10409864 |
Anomaly detection algorithms: Comparative analysis and explainability perspectives.Darab, S., Allipilli, H., Ghani, S., Changaramkulath, H., Koneru, S., Broneske, D., & Saake, G. (2023).Anomaly detection algorithms: Comparative analysis and explainability perspectives. In D. Benavides-Prado et al. (Hrsg.), Data Science and Machine Learning, 21st Australasian Conference, AusDM 2023, Auckland, New Zealand, December 11–13, 2023, Proceedings (S. 90-104). Singapore: Springer Nature. |
The sound of respondents: predicting respondents’ level of interest in questions with voice data in smartphone surveys.Höhne, J. K., Kern, C., Gavras, K., & Schlosser, S. (2023).The sound of respondents: predicting respondents’ level of interest in questions with voice data in smartphone surveys. Quality & Quantity, International Journal of Methodology, 57(6). https://doi.org/10.1007/s11135-023-01776-8 Abstract
Web surveys completed on smartphones open novel ways for measuring respondents’ attitudes, behaviors, and beliefs that are crucial for social science research and many adjacent research fields. In this study, we make use of the built-in microphones of smartphones to record voice answers in a smartphone survey and extract non-verbal cues, such as amplitudes and pitches, from the collected voice data. This allows us to predict respondents’ level of interest (i.e., disinterest, neutral, and high interest) based on their voice answers, which expands the opportunities for researching respondents’ engagement and answer behavior. [...] Full abstract: https://doi.org/10.1007/s11135-023-01776-8 |
WISHFUL - Website extraction of Institutional Sources with Heterogeneous Factors and User-Driven Linkage.Shahania, S., Spiliopoulou, M., & Broneske, D. (2023).WISHFUL - Website extraction of Institutional Sources with Heterogeneous Factors and User-Driven Linkage. In Delir Haghighi, P. et al. (Hrsg.), Information Integration and Web Intelligence (iiWAS 2023) (S. 20-26). Cham: Springer. https://doi.org/10.1007/978-3-031-48316-5_3 Abstract
Extracting information from diverse websites is increasingly important, especially for analyzing vast data sets to detect trends, gain insights. By studying job ads, researchers can monitor employer demand shifts, assisting policymakers in aiding affected workers and industries. However, extraction faces challenges like varied website formats, dynamic content, and duplicate data. This study introduces a method for extracting data from diverse private university websites involving keyword identification, website categorization, and extraction pipelines. |
Does the higher education experience affect political interest, efficacy, and participation? Comparing dropouts to graduates and ‘non-starters’.Mishra, S., Klein, D., & Müller, L. (2023).Does the higher education experience affect political interest, efficacy, and participation? Comparing dropouts to graduates and ‘non-starters’. European Journal of Higher Education. https://doi.org/10.1080/21568235.2023.2276853 |
Large language models and low-resource languages: An examination of Armenian NLP.Avetisyan, H., & Broneske, D. (2023).Large language models and low-resource languages: An examination of Armenian NLP. Findings of the Association for Computational Linguistics: IJCNLP-AACL 2023 (Findings), 2023, 199-210. |
Pragmatische Tools oder kreativer Umgang? Qualitative Methoden in der anwendungsorientierten Hochschulforschung.Behrmann, L., İkiz-Akıncı, D., & Rückamp, V. (2023).Pragmatische Tools oder kreativer Umgang? Qualitative Methoden in der anwendungsorientierten Hochschulforschung. Forum Qualitative Sozialforschung 24(3). www.qualitative-research.net, https://doi.org/10.17169/fqs-24.3.3968 (Abgerufen am: 26.09.2023) (online first). https://doi.org/10.17169/fqs-24.3.3968 |
A strategy for retrospective evaluation of students SQL learning engagements.Obionwu, C. V., Kalu, K. O., Blockhaus, P., Broneske, D., & Saake, G. (2023).A strategy for retrospective evaluation of students SQL learning engagements. In IEEE Institute of Electrical and Electronic Engineers (Hrsg.), 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME 2023) (S. 1-7). Tenerife, Spain: IEEE. https://doi.org/10.1109/ICECCME57830.2023.10252347 |
Optical image recognition strategy for keyword extraction and page ranking for slide recommendation system.Obionwu, C. V., Abbas, S. M. L., Padmanabhan, V., Tiwari, T., Broneske, D., & Saake, G. (2023).Optical image recognition strategy for keyword extraction and page ranking for slide recommendation system. In IEEE Institute of Electrical and Electronic Engineers (Hrsg.), 2023 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) (S. 1-6). Tenerife, Spain: IEEE. https://doi.org/10.1109/ICECCME57830.2023.10252423 |
FPGA-integrated bag of little bootstraps accelerator for approximate database query processing.Burtsev, V., Wilhelm, M., Drewes, A., Gurumurthy, B., Broneske, D., Pionteck, T., & Saake, G. (2023).FPGA-integrated bag of little bootstraps accelerator for approximate database query processing. In F. Palumbo, G. Keramidas, N. Voros, & P. C. Diniz (Hrsg.), Applied Reconfigurable Computing. Architectures, Tools, and Applications (ARC 2023). Lecture Notes in Computer Science (S. 115-130). Cham: Springer. |
Enhancing AutoNLP with fine-tuned BERT models: An evaluation of text representation methods for AutoPyTorch.Safikhani, P., & Broneske, D. (2023).Enhancing AutoNLP with fine-tuned BERT models: An evaluation of text representation methods for AutoPyTorch. In D. C. Wyld & D. Nagamalai (Hrsg.), Computer Science & Information Technology (CS & IT) (S. 23-38). Chennai, Tamil Nadu, India: AIRCC Publishing Corporation. |
Decoding the encoded - Linguistic secrets of language models: A systematic literature review.Avetisyan, H., & Broneske, D. (2023).Decoding the encoded - Linguistic secrets of language models: A systematic literature review. In D. C. Wyld & D. Nagamalai (Hrsg.), Computer Science & Information Technology (CS & IT) (S. 67-88). Chennai, Tamil Nadu, India: AIRCC Publishing Corporation. |
Investigating respondents’ willingness to participate in video-based web surveys.Höhne, J. K., Ziller, C., & Lenzner, T. (2023).Investigating respondents’ willingness to participate in video-based web surveys. International Journal of Market Research. https://doi.org/10.1177/14707853231198788 (Abgerufen am: 06.09.2023) (online first). https://doi.org/10.1177/14707853231198788 |
Kontakt
