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Entity-Level Stream Classification: Exploiting Entity Similarity to Label the Future Observations Referring to an Entity.

, , , , , , , and . DSAA, page 246-255. IEEE, (2018)

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Active feature acquisition on data streams under feature drift., , , , , and . Ann. des Télécommunications, 75 (9-10): 597-611 (2020)Active feature acquisition on data streams under feature drift, , , , , and . Annals of Telecommunications, (Jul 8, 2020)Resource management for model learning at entity level, , , , , , and . Annals of Telecommunications, (Aug 29, 2020)Active Feature Acquistion for Opinion Stream Classification under Drift, , , , and . Proceedings of the Workshop on Interactive Adaptive Learning (IAL 2019), page 108--111. CEUR Workshop, (2019)Productive teaming under uncertainty: when a human and a machine classify objects together., , , , , , , , , and . ARSO, page 9-14. IEEE, (2023)Reducing Missingness in a Stream through Cost-Aware Active Feature Acquisition., , and . DSAA, page 1-10. IEEE, (2022)How to select information that matters: a comparative study on active learning strategies for classification., , and . I-KNOW, page 2:1-2:8. ACM, (2015)Challenges for Active Feature Acquisition and Imputation on Data Streams., , and . IAL@PKDD/ECML, volume 3470 of CEUR Workshop Proceedings, page 9-13. CEUR-WS.org, (2023)Entity-Level Stream Classification: Exploiting Entity Similarity to Label the Future Observations Referring to an Entity., , , , , , , and . DSAA, page 246-255. IEEE, (2018)Predicting polarities of entity-centered documents without reading their contents., , , , and . SAC, page 525-528. ACM, (2018)