RULKKG: Estimating User’s Knowledge Gain in Search-as-Learning Using Knowledge Graphs
Author:
Affiliation:
1. I3S Lab, CNRS, UMR 7271, Université Côte d'Azur, France
2. I3S Lab, CNRS, UMR 7271, Inria, Université Côte d'Azur, France
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3627508.3638331
Reference35 articles.
1. Peter Bailey Liwei Chen Scott Grosenick Li Jiang Yan Li Paul Reinholdtsen Charles Salada Haidong Wang and Sandy Wong. 2012. User task understanding: a web search engine perspective. In NII shonan meeting on whole-session evaluation of interactive information retrieval systems Kanagawa Japan.
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3. N. J. Belkin R. N. Oddy and H. M. Brooks. 1982. Ask for information retrieval: Part I. background and theory. Issue 2. https://doi.org/10.1108/eb026722
4. Horst Bunke. 2000. Graph Matching : Theoretical Foundations, Algorithms, and Applications. Algorithmica 2000 (2000). Issue 2.
5. REBEL: Relation Extraction By End-to-end Language generation
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