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Entity-level stream classification: exploiting entity similarity to label the future observations referring to an entity

, , , , , , , и . International Journal of Data Science and Analytics, (2019)
DOI: 10.1007/s41060-019-00177-1

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Christian Beyer

Christian Beyer

Christian Beyer

Christian Beyer

Christian Beyer

 

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Active Feature Acquistion for Opinion Stream Classification under Drift, , , , и . Proceedings of the Workshop on Interactive Adaptive Learning (IAL 2019), стр. 108--111. CEUR Workshop, (2019)Active feature acquisition on data streams under feature drift, , , , , и . Annals of Telecommunications, (08.07.2020)Resource management for model learning at entity level, , , , , , и . Annals of Telecommunications, (29.08.2020)Productive teaming under uncertainty: when a human and a machine classify objects together., , , , , , , , , и . ARSO, стр. 9-14. IEEE, (2023)Reducing Missingness in a Stream through Cost-Aware Active Feature Acquisition., , и . DSAA, стр. 1-10. IEEE, (2022)Active feature acquisition on data streams under feature drift., , , , , и . Ann. des Télécommunications, 75 (9-10): 597-611 (2020)How to select information that matters: a comparative study on active learning strategies for classification., , и . I-KNOW, стр. 2:1-2:8. ACM, (2015)Challenges for Active Feature Acquisition and Imputation on Data Streams., , и . IAL@PKDD/ECML, том 3470 из CEUR Workshop Proceedings, стр. 9-13. CEUR-WS.org, (2023)Predicting polarities of entity-centered documents without reading their contents., , , , и . SAC, стр. 525-528. ACM, (2018)Entity-Level Stream Classification: Exploiting Entity Similarity to Label the Future Observations Referring to an Entity., , , , , , , и . DSAA, стр. 246-255. IEEE, (2018)