Name
Abstract | ||
|---|---|---|
ABSTRACTThe aim of this workshop is to stimulate research on human-computer interaction challenges in data science. We invite researchers and practitioners interested in understanding how to optimize the human-computer cooperation and how to minimize human effort along the data science pipeline in a wide range of data science tasks and real-life applications. One over-arching challenge is to raise the level of abstraction of human-computer interaction to more sophisticated interaction models that better reflect a human's conceptual model and understanding. This workshop will bring together the interdisciplinary researchers from academia, research labs and practice to share, exchange, learn, and develop preliminary results, new concepts, ideas, principles, and methodologies on understanding and improving human-computer interaction for cost-effective development of data science models and for knowledge discovery. We expect the workshop to help develop and grow a strong community of researchers who are interested in this topic, and yield future collaborations and scientific exchanges across the relevant areas of data mining, machine learning, data and knowledge management, human-machine interaction, and user interfaces. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1145/3447548.3469476 | Knowledge Discovery and Data Mining |
Keywords | DocType | Citations |
Data Science, Human-in-the-Loop | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Eduard Constantin Dragut | 1 | 201 | 21.55 |
| Yunyao Li | 2 | 530 | 37.81 |
| Ling-ling Yan | 3 | 1273 | 70.78 |
| Slobodan Vucetic | 4 | 637 | 56.38 |