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- W1565932570 abstract "In Senseval workshops for evaluating WSD systems [1,4,9], no one system or system type (classifier algorithm, type of system ensemble, extracted feature set, lexical knowledge source etc.) has been discovered that resolves all ambiguous words into their senses in a superior way. This paper presents a novel method for selecting the best system for target word based on readily available word features (number of senses, average amount of training per sense, dominant sense ratio). Applied to Senseval-3 and Senseval-2 English lexical sample state-of-art systems, a net gain of approximately 2.5 – 5.0% (respectively) in average precision per word over the best base system is achieved. The method can be applied to any base system or target word in any language." @default.
- W1565932570 created "2016-06-24" @default.
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- W1565932570 date "2006-01-01" @default.
- W1565932570 modified "2023-09-25" @default.
- W1565932570 title "Building an Optimal WSD Ensemble Using Per-Word Selection of Best System" @default.
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- W1565932570 doi "https://doi.org/10.1007/11892755_89" @default.
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