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- W2950796788 abstract "This paper investigates the effects of data size and frequency range on distributional semantic models. We compare the performance of a number of representative models for several test settings over data of varying sizes, and over test items of various frequency. Our results show that neural network-based models underperform when the data is small, and that the most reliable model over data of varying sizes and frequency ranges is the inverted factorized model." @default.
- W2950796788 created "2019-06-27" @default.
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- W2950796788 date "2016-09-27" @default.
- W2950796788 modified "2023-09-27" @default.
- W2950796788 title "The Effects of Data Size and Frequency Range on Distributional Semantic Models" @default.
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