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Neural Feature Selection for Learning to Rank
LEarning TO Rank (LETOR) is a research area in the field of Information Retrieval (IR) where machine learning models are employed to rank a set of items.
Extractive Summarization under Strict Length Constraints
In this paper we report a comparison of various techniques for single-document extractive summarization under strict length budgets, which is a common commercial use case (e. g. summarization of news articles by news aggregators).
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