In this paper, we report on our proposed approach towards a standardized description for systems combining machine learning (ML) components with techniques developed by the Semantic Web (SW) community (SWeMLS), which is one of lessons learned from our large-scale survey (476 papers) on the topic. We elaborate the key information that should be described of SWeMLS and selected methods to support its documentation.
|Title of host publication||Proceedings of Poster and Demo Track and Workshop Track of the 18th International Conference on Semantic Systems co-located with 18th International Conference on Semantic Systems (SEMANTiCS 2022)|
|Place of Publication||Aachen|
|Publication status||Published - 2022|
|Event||18th International Conference on Semantic Systems, SEMPDW 2022 - Vienna, Austria|
Duration: 13 Sept 2022 → 15 Sept 2022
|Series||CEUR Workshop Proceedings|
|Conference||18th International Conference on Semantic Systems, SEMPDW 2022|
|Period||13/09/22 → 15/09/22|
Bibliographical noteFunding Information:
This work is supported by the FFG Project OBARIS (Grant Agreement
This work is supported by the FFG Project OBARIS (Grant Agreement No 877389).
© 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)
- machine learning
- neuro-symbolic systems
- semantic web