Towards Knowledge Acquisition of Metadata on AI Progress

Zhiyu Chen, Mohamed Trabelsi, Brian D. Davison and Jeff Heflin.

Poster Paper (5 pages)
Author's version: PDF (231KB)

Abstract
We propose an ontology to help AI researchers keep track of the scholarly progress of AI related tasks such as natural language processing and computer vision. We first define the core entities and relations in the proposed Machine Learning Progress Ontology (MLPO). Then we describe how to use the techniques in natural language processing to construct a Machine Learning Progress Knowledge Base (MPKB) that can support various downstream tasks.

In Proceedings of the ISWC 2020 Demos and Industry Tracks: From Novel Ideas to Industrial Practice, co-located with the 19th International Semantic Web Conference (ISWC 2020), CEUR Workshop Proceedings, Vol. 2721, pp. 232-237, November 2020.

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Last modified: 2 November 2020
Brian D. Davison