Publications

by SALIENT project members

2021

Yu, R., Tang, R., Rokicki, M., Gadiraju, U., & Dietze, S. (2021).
Topic-independent modeling of user knowledge in informational search sessions
Information Retrieval Journal24(3), 240–268. doi.org/10.1007/s10791-021-09391-7

Otto, C., Yu, R., Pardi, G., von Hoyer, J., Rokicki, M., Hoppe, A., Holtz, P., Kammerer, Y., Dietze, S., & Ewerth, R. (2021).
Predicting Knowledge Gain During Web Search Based on Multimedia Resource Consumption. In I. Roll, D. S. McNamara, S. A. Sosnovsky, R. Luckin, & V. Dimitrova, Artificial Intelligence in Education - 22nd International Conference, AIED 2021, Utrecht, The Netherlands, June 14-18, 2021, Proceedings, Part I (Vol. 12748, pp. 318–330). Springer. https://doi.org/10.1007/978-3-030-78292-4_26 [preprint]


2020

Hoppe, A., Yu, R., Kammerer, Y., Salmerón, L.:
IWILDS'20: 1st International Workshop on Investigating Learning During Web Search. 29th ACM International Conference on Information and Knowledge Management (CIKM) 2020: 3535-3536. [Publisher, workshop website]

Otto, C., Springstein, M., Anand, A., Ewerth, R.:
Characterization and classification of semantic image-text relations. International Journal of Multimedia Information Retrieval 9(1): 31-45 (2020) [Publisher, pdf]

Pardi, G., von Hoyer, J., Holtz, P., Kammerer, Y.:
The Role of Cognitive Abilities and Time Spent on Texts and Videos in a Multimodal Searching as Learning Task. ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR) 2020: 378-382 [Publisher] Best Short Paper Award.

Yu, R.:
Improving Knowledge Accessibility on the Web - from Knowledge Base Augmentation to Search as Learning. PhD Thesis. University of Düsseldorf, Germany, 2020 [Repository, pdf]

Kammerer, Y., & Brand-Gruwel, S. (2020).
Trainings and tools to foster source credibility evaluation during web search. In W.-T. Fu & H. van Oostendorp (Eds.), Understanding and improving information search (pp. 213-243). Cham: Springer. (Publisher)

Lewandowski, D., & Kammerer, Y. (in press).
Factors influencing viewing behaviour on search engine results pages: a review of eye-tracking research. Behaviour & Information Technology. (Publisher)

Dimitar Dimitrov, Erdal Baran, Pavlos Fafalios, Ran Yu, Xiaofei Zhu, Matthäus Zloch, and Stefan Dietze, 
TweetsCOV19 — A Knowledge Base of Semantically Annotated Tweets about the COVID-19 Pandemic, CIKM 2020 Resource Track. (pdf | website)

 

2019

Ewerth, R., Dietze, S., Hoppe, A., Yu, R.:
SALMM'19: First International Workshop on Search as Learning with Multimedia Information. ACM Multimedia 2019: 2724-2725
[pdf]

von Hoyer, J., Pardi, G., Kammerer, Y., & Holtz, P.:
Metacognitive Judgments in Searching as Learning (SAL) Tasks Insights on (Mis-) Calibration, Multimedia Usage, and Confidence. Proceedings of the 1st International Workshop on Search as Learning with Multimedia Information (pp. 3-10). ACM. https://dx.doi.org/10.1145/3347451.3356730
[pdf]

Shi, J., Otto, C., Hoppe, A., Holtz, P., Ewerth, R.:
Investigating Correlations of Automatically Extracted Multimodal Features and Lecture Video Quality. Proceedings of the 1st International Workshop on Search as Learning with Multimedia Information (pp. 11-19). ACM. https://dx.doi.org/10.1145/3347451.3356731
[pdf]

Otto, C., Springstein, M., Anand, A., & Ewerth, R.:
Understanding, Categorizing and Predicting Semantic Image-Text Relations. ACM International Conference on Multimedia Retrieval (ICMR), Ottawa, Canada, 168-176, 2019. "Best Paper Award"
[pdf]

Otto, C., Holzki, S., & Ewerth, R.:
''Is this an example image?'' - Predicting the Relative Abstractness Level of Image and Text. In Proceedings of European Conference on Information Retrieval (ECIR), ECIR (1), Cologne, Germany, 711-725, 2019
[https://arxiv.org/abs/1901.07878]

Zhou H., Otto C., Ewerth R.:
Visual Summarization of Scholarly Videos Using Word Embeddings and Keyphrase Extraction. In: Doucet A., Isaac A., Golub K., Aalberg T., Jatowt A. (eds) Digital Libraries for Open Knowledge. TPDL 2019. Lecture Notes in Computer Science, vol 11799. Springer, Cham
[pdf]

Pardi, G., Kammerer, Y., Gerjets, P.:
Search and Justification Behavior During Multimedia Web Search for Procedural Knowledge , Companion Publication of the 10th ACM Conference on Web Science, WebSci 2019, Boston, MA, USA, June 30 - July 03, 2019. , 17–20, 2019
[pdf]

Yu, R., Gadiraju, U., Fetahu, B., Lehmberg, O., Ritze, D., & Dietze, S.:
KnowMore - knowledge base augmentation with structured web markup. Semantic Web 10(1), 159-180, 2019.
[pdf]

Davari, M., Yu, R., Dietze, S.:
Understanding The Influence of Task Difficulty on Search Behavior in Digital Libraries. The 2nd International Workshop on ExplainAble Recommendation and Search (EARS), 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Paris, France, 2019.
[pdf]

 

2018

Yu, R., Gadiraju, U., Holtz, P., Rokicki, M., Kemkes, P., & Dietze, S.:
Predicting User Knowledge Gain in Informational Search Sessions, full research track paper at 41st International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2018), Ann Arbor Michigan, U.S.A. July 8-12, 2018, ACM.
[ https://arxiv.org/abs/1805.00823 ]

Gadiraju, U., Yu, R., Dietze, S., & Holtz, P.:
Analyzing Knowledge Gain of Users in Informational Search Sessions on the Web, full research track paper at ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR2018), New Brunswick, NJ, US, 11-15 March 2018, ACM.
[ pdf ]

Medrek, J., Otto, C., & Ewerth, R.:
Recommending Scientific Videos based on Metadata Enrichment using Linked Open Data
In Proceedings of International Conference on Theory and Practice of Digital Libraries (TPDL), 286-292, Porto, Portugal, 2018.
[ https://arxiv.org/abs/1806.07309 ]

Hoppe, A., Holtz, P., Kammerer, Y. , Yu, R., Dietze, S., & Ewerth, R.:
Current Challenges for Studying Search as Learning Processes
Linked Learning Workshop – Learning and Education with Web Data (LILE), in conjunction with ACM Conference on Web Science, Amsterdam, 2018
[ pdf ]

Yu, R. , Gadiraju, U., & Dietze, S.:
Detecting, Understanding and Supporting Everyday Learning in Web Search. Workshop on Learning & Education with Web Data (LILE), 10th ACM Conference on Web Science (WebSci), 2018.
pdf ]

Kammerer, Y., Brand-Gruwel, S., & Jarodzka, H.:
The future of learning by searching the Web: mobile, social, and multimodal. Frontline Learning Research, 6, 81-91, 2018.
[ pdf ]