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Can I read Learning to Rank for Information Retrieval and Natural Language Processing (Synthesis Lectures on Human Language Technology, 12) on EtoBox?
Learning to Rank for Information Retrieval and Natural Language Processing (Synthesis Lectures on Human Language Technology, 12) by Hang Li is a nonfiction available to read on EtoBox.
What is Learning to Rank for Information Retrieval and Natural Language Processing (Synthesis Lectures on Human Language Technology, 12) about?
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. The author begins by showing that various ranking problems in information retrieval and natural language processing can be formalized as two basic ranking tasks, namely ranking creation (or simply ranking) and ranking aggregation. In ranking creation, given a request, one wants to generate a ranking list of offerings based on the features derived from the request and the offerings. In ranking aggregation, given a request, as well as a number of ranking lists of offerings, one wants to generate a new ranking list of the offerings. Ranking creation (or ranking) is the major problem in learning to rank. It is usually formalized as a supervised learning task. The author gives detailed explanations on learning for ranking creation
Who reads Learning to Rank for Information Retrieval and Natural Language Processing (Synthesis Lectures on Human Language Technology, 12)?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Hang Li
- Publisher
- Morgan & Claypool Publishers
- Published
- 2011
- Language
- EN
- ISBN
- 9781627055857
- Category
- nonfiction
- Subjects
- Mathematics, Science, Stem
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