Data Science for Smart Culture: Harnessing Human Semantics at Scale

Speaker:  Lora Aroyo – New York City, NY, United States
Topic(s):  Human Computer Interaction


Software systems are becoming ever more intelligent and more useful, but the way we interact with these machines too often reveals that they don’t actually understand people. Knowledge Representation and Semantic Web focus on the scientific challenges involved in providing human knowledge in machine-readable form. However, we observe that various types of human knowledge cannot yet be captured by machines, especially when dealing with wide ranges of real-world tasks and contexts. The key scientific challenge is to provide an approach to capturing human knowledge in a way that is scalable and adequate to real-world needs. Human Computation has begun to scientifically study how human intelligence at scale can be used to methodologically improve machine-based knowledge and data management. My research is focusing on understanding human computation for improving how machine-based systems can acquire, capture and harness human knowledge and thus become even more intelligent. In this talk I will focus on use cases related to smart culture, e.g. enrichment of cultural heritage collections of artworks, videos, newspapers, etc. I will show how the CrowdTruth framework ( facilitates data collection, processing and analytics of human computation knowledge. Processing real-world data with the crowd leaves one thing absolutely clear - there is no single notion of truth, but rather a spectrum that has to account for context, opinions, perspectives and shades of grey. CrowdTruth is a new framework for processing of human semantics drawn more from the notion of consensus then from set theory. 

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About this Lecture

Number of Slides:  59
Duration:  50 minutes
Languages Available:  English
Last Updated: 

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