By a News Reporter-Staff News Editor at Information Technology Newsweekly -- Fresh data on Information Technology are presented in a new report. According to news originating from Boca Raton, Florida, by VerticalNews correspondents, research stated, "Traditional active learning methods require the labeler to provide a class label for each queried instance. The labelers are normally highly skilled domain experts to ensure the correctness of the provided labels, which in turn results in expensive labeling cost."
Our news journalists obtained a quote from the research from Florida Atlantic University, "To reduce labeling cost, an alternative solution is to allow nonexpert labelers to carry out the labeling task without explicitly telling the class label of each queried instance. In this paper, we propose a new active learning paradigm, in which a nonexpert labeler is only asked 'whether a pair of instances belong to the same class', namely, a pairwise label homogeneity. Under such circumstances, our active learning goal is twofold: (1) decide which pair of instances should be selected for query, and (2) how to make use of the pairwise homogeneity information to improve the active learner. To achieve the goal, we propose a 'Pairwise Query on Max-flow Paths' strategy to query pairwise label homogeneity from a nonexpert labeler, whose query results are further used to dynamically update a Min-cut model (to differentiate instances in different classes). In addition, a 'Confidence-based Data Selection' measure is used to evaluate data utility based on the Min-cut model's prediction results. The selected instances, with inferred class labels, are included into the labeled set to form a closed-loop active learning process."
According to the news editors, the research concluded: "Experimental results and comparisons with state-of-the-art methods demonstrate that our new active learning paradigm can result in good performance with nonexpert labelers."
For more information on this research see: Active Learning without Knowing Individual Instance Labels: A Pairwise Label Homogeneity Query Approach. IEEE Transactions on Knowledge and Data Engineering, 2014;26(4):808-822. IEEE Transactions on Knowledge and Data Engineering can be contacted at: Ieee Computer Soc, 10662 Los Vaqueros Circle, PO Box 3014, Los Alamitos, CA 90720-1314, USA. (Institute of Electrical and Electronics Engineers - www.ieee.org/; IEEE Transactions on Knowledge and Data Engineering - ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=69)
The news correspondents report that additional information may be obtained from Y.F. Fu, Florida Atlantic Univ, Dept. of Comp & Elect Engn & Comp Sci, Boca Raton, FL 33431, United States. Additional authors for this research include B. Li, X.Q. Zhu and C.Q. Zhang.
Keywords for this news article include: Florida, Boca Raton, United States, Information Technology, North and Central America
Our reports deliver fact-based news of research and discoveries from around the world. Copyright 2014, NewsRx LLC