Categories |
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SEGMENTATION
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NLP
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MACHINE LEARNING
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About |
Sentences are basic units of the written language. Detecting the beginning and end of sentences, or sentence boundary detection (SBD), is the foundational first step in many Natural Language Processing (NLP) applications such as POS tagging; syntactic, semantic, and discourse parsing; information extraction; or machine translation. Despite its important role in NLP, Sentence Boundary Detection has so far not received enough attention. Previous research in the area has been confined to only formal texts (news, European Parliament proceedings, etc.) where existing rule-based and machine learning approaches are extremely accurate so-long the data is perfectly clean. No sentence boundary detection research to date has addressed the problem in noisy texts extracted automatically from machine-readable files (generally PDF file format) such as financial documents. |
Call for Papers |
We list some possible topics below with the research tracks of The Web Conference, but the submissions from participants are not limited to these topics.
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Credits and Sources |
[1] Shared Task - FinSBD-3 : The 3rd Shared Task on Structure Boundary Detection, an extension of Sentence Boundary Detection |