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- W2251769296 abstract "In the current fast-paced world, people tend to possess limited knowledge about things from the past. For example, some young users may not know that Walkman played similar function as iPod does nowadays. In this paper, we approach the temporal correspondence problem in which, given an input term (e.g., iPod) and the target time (e.g. 1980s), the task is to find the counterpart of the query that existed in the target time. We propose an approach that transforms word contexts across time based on their neural network representations. We then experimentally demonstrate the effectiveness of our method on the New York Times Annotated Corpus." @default.
- W2251769296 created "2016-06-24" @default.
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- W2251769296 date "2015-01-01" @default.
- W2251769296 modified "2023-10-16" @default.
- W2251769296 title "Omnia Mutantur, Nihil Interit: Connecting Past with Present by Finding Corresponding Terms across Time" @default.
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- W2251769296 doi "https://doi.org/10.3115/v1/p15-1063" @default.
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