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QUARE: 1st Workshop on Measuring the Quality of Explanations in Recommender Systems.

, , , , and . SIGIR, page 3478-3481. ACM, (2022)

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Understanding the Role of Explanation Modality in AI-assisted Decision-making., , and . UMAP, page 223-233. ACM, (2022)Machine-Crowd Annotation Workflow for Event Understanding Across Collections and Domains.. ESWC, volume 9678 of Lecture Notes in Computer Science, page 813-823. Springer, (2016)Studying Topical Relevance with Evidence-based Crowdsourcing., , , , , , , and . CIKM, page 1253-1262. ACM, (2018)Framing is Mightier than the Sword: Detection of Episodic and Thematic Framing in News Media., , , , , , , , , and . Hum. Comput., 11 (1): 1-28 (2024)DIVE into the event-based browsing of linked historical media., , , , , , and . J. Web Semant., (2015)Workshop on Explainable User Models and Personalized Systems (ExUM 2021)., , , , , and . UMAP (Adjunct Publication), page 211-212. ACM, (2021)Harnessing Diversity in Crowds and Machines for Better NER Performance., and . ESWC (1), volume 10249 of Lecture Notes in Computer Science, page 289-304. (2017)QUARE: 2nd Workshop on Measuring the Quality of Explanations in Recommender Systems., , , , , , and . RecSys, page 1241-1243. ACM, (2023)Someone really wanted that song but it was not me!: Evaluating Which Information to Disclose in Explanations for Group Recommendations., , and . IUI Companion, page 85-86. ACM, (2020)Evaluating explainable social choice-based aggregation strategies for group recommendation., , , , , , , and . User Model. User Adapt. Interact., 34 (1): 1-58 (March 2024)