[PDF.94tp] Learning to Rank for Information Retrieval and Natural Language Processing (Synthesis Lectures on Human Language Technology)
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Learning to Rank for Information Retrieval and Natural Language Processing (Synthesis Lectures on Human Language Technology)
[PDF.th39] Learning to Rank for Information Retrieval and Natural Language Processing (Synthesis Lectures on Human Language Technology)
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| #4781774 in Books | 2011-04-22 | Original language:English | PDF # 1 | 9.25 x.26 x7.50l,.46 | File type: PDF | 114 pages||0 of 0 people found the following review helpful.| quick primer on methods for learning to rank techniques and theoritical underpinnings|By ravidvs|Provides a survey of methods for learning to rank, the author focuses on problem formulations and presents loss functions (the metrics that are optimized in the learning process) in a very intuitive manner. I am a researcher in this field, a survey of software (both open source and
Learning to rank refers to machine learning techniques for training the model in a ranking task. Learning to rank is useful for many applications in information retrieval, natural language processing, and data mining. Intensive studies have been conducted on the problem recently and significant progress has been made. This lecture gives an introduction to the area including the fundamental problems, existing approaches, theories, applications, and future work.
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You can specify the type of files you want, for your device.Learning to Rank for Information Retrieval and Natural Language Processing (Synthesis Lectures on Human Language Technology) | Hang Li. I have read it a couple of times and even shared with my family members. Really good. Couldnt put it down.