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- W2512192886 abstract "Extracting bio-entity relations has emerged as an important task due to the ever-growing number of bio-medical documents. In this paper, we present a simple and novel representation for extracting bio-entity relationships. The state-of-theart systems for such tasks rely on word based representations and variations of linguistic driven features. In contrast, we model bio-text by the most basic character based string representation with a family of string kernels. This eliminates time consuming parsing, issue of rare words and domain specific pre-processing. This simple representation makes our approach fast and flexible for any bio-NLP dataset. We demonstrate comparable performance and faster computation time of our approach versus previous state-of-the-art kernel methods." @default.
- W2512192886 created "2016-09-16" @default.
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- W2512192886 date "2016-01-01" @default.
- W2512192886 modified "2023-10-12" @default.
- W2512192886 title "Character based String Kernels for Bio-Entity Relation Detection" @default.
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- W2512192886 doi "https://doi.org/10.18653/v1/w16-2908" @default.
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