Yaoyong Li


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Evaluating Evaluation Metrics for Ontology-Based Applications: Infinite Reflection
Diana Maynard | Wim Peters | Yaoyong Li
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

In this paper, we discuss methods of measuring the performance of ontology-based information extraction systems. We focus particularly on the Balanced Distance Metric (BDM), a new metric we have proposed which aims to take into account the more flexible nature of ontologically-based applications. We first examine why traditional Precision and Recall metrics, as used for flat information extraction tasks, are inadequate when dealing with ontologies. We then describe the Balanced Distance Metric (BDM) which takes ontological similarity into account. Finally, we discuss a range of experiments designed to test the accuracy and usefulness of the BDM when compared with traditional metrics and with a standard distance-based metric.


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Using Uneven Margins SVM and Perceptron for Information Extraction
Yaoyong Li | Kalina Bontcheva | Hamish Cunningham
Proceedings of the Ninth Conference on Computational Natural Language Learning (CoNLL-2005)

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Perceptron Learning for Chinese Word Segmentation
Yaoyong Li | Chuanjiang Miao | Kalina Bontcheva | Hamish Cunningham
Proceedings of the Fourth SIGHAN Workshop on Chinese Language Processing


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The SVM With Uneven Margins and Chinese Document Categorization
Yaoyong Li | John Shawe-Taylor
Proceedings of the 17th Pacific Asia Conference on Language, Information and Computation