Abstract
In this chapter, we introduce some applications of learning to rank. The major purpose is to demonstrate how to use an existing learning-to-rank algorithm to solve a real ranking problem. In particular, we will take question answering, multimedia retrieval, text summarization, online advertising, etc. as examples, for illustration. One will see from these examples that the key step is to extract effective features for the objects to be ranked by considering the unique properties of the application, and to prepare a set of training data. Then it becomes straightforward to train a ranking model from the data and use it for ranking new objects.
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Liu, TY. (2011). Applications of Learning to Rank. In: Learning to Rank for Information Retrieval. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14267-3_14
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DOI: https://doi.org/10.1007/978-3-642-14267-3_14
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