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Found 3 papers, 0 papers with code
Distinguishing Between Foreground and Background Events in News
Determining whether an event in a news article is a foreground or background event would be useful in many natural language processing tasks, for example, temporal relation extraction, summarization, or storyline generation.
Improving the Identification of the Discourse Function of News Article Paragraphs
Identifying the discourse structure of documents is an important task in understanding written text.
Automatically Detecting the Position and Type of Psychiatric Evaluation Report Sections
To model conventions for section order, we integrated these n-gram models with a Hierarchical Hidden Markov Model (HHMM) representing the probabilities of observed section orders found in the corpus, and then used this HHMM n-gram model in a decoding framework to infer the most likely section boundaries and section types for documents with their section labels removed.
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