Search Results for author:
Found 3 papers, 3 papers with code
CPTAM: Constituency Parse Tree Aggregation Method
This paper adopts the truth discovery idea to aggregate constituency parse trees from different parsers by estimating their reliability in the absence of ground truth.
Truth Discovery in Sequence Labels from Crowds
The proposed Aggregation method for Sequential Labels from Crowds ($AggSLC$) jointly considers the characteristics of sequential labeling tasks, workers' reliabilities, and advanced machine learning techniques.
OptSLA: an Optimization-Based Approach for Sequential Label Aggregation
Our results show that the proposed OptSLA outperforms the state-of-the-art aggregation methods, and the results are easier to interpret.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
