@inproceedings{dced9032ee4f4f0d83ed499f0ff4fdf4,
title = "Augmented query strategies for active learning in stream data mining",
abstract = "Active learning is used in situations where the amount of unlabeled data is abundant but it is costly to manually label the data. So, depending on our available budget, from all unlabeled instances we are to select only a subset of them to ask the oracle for manual labeling. Thus, the query strategy, i.e., how relevant instances are selected to be sent to the oracle, plays an important role in active learning. Though active learning is a very established research area, only a few research works have been done on it in the context of stream data mining. Active learning for stream data is more challenging than for static data because the repetition of queries is not feasible as revisiting the data is almost impossible. In this paper, we propose two augmented query strategies for active learning in stream data mining, namely, Margin Sampling with Variable Uncertainty (MSVU) and Entropy Sampling with Uncertainty using Randomization (ESUR). These two strategies are derived and improved from the existing methods of Variable Uncertainty (VU) and Uncertainty using Randomization (UR) respectively. We evaluate the effectiveness of our proposed MSVU and ESUR strategies by comparing them against the original VU and UR on 6 different datasets using two base classifiers: Leveraging Bagging (LB) and Single Classifier Drift (SCD). Experimental results show that our proposed strategies offer promising outcomes for various datasets and detecting concept drift in the data.",
keywords = "Active learning, Query strategy, Stream data mining",
author = "Faisal, {Mustafa Amir} and Zeyar Aung and Woon, {Wei Lee} and Davor Svetinovic",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2014.; 21st International Conference on Neural Information Processing, ICONIP 2014 ; Conference date: 03-11-2014 Through 06-11-2014",
year = "2014",
doi = "10.1007/978-3-319-12643-2_53",
language = "British English",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "431--438",
editor = "Loo, {Chu Kiong} and Yap, {Keem Siah} and Wong, {Kok Wai} and Andrew Teoh and Kaizhu Huang",
booktitle = "Neural Information Processing - 21st International Conference, ICONIP 2014, Proceedings",
address = "Germany",
}