Data-Driven Information Retrieval Task
(Redirected from IR Learning to Rank)
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A Data-Driven Information Retrieval Task is an information retrieval task that is a data-driven task.
- Context:
- It can be solved by a Data-Driven IR System (that implements a data-driven IR algorithm).
- It can range from being a Supervised IR Task to being a Semi-Supervised IR Task to being an Unsupervised IR Task.
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- Example(s):
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- Counter-Example(s):
- See: Learning-to-Rank Task, IR System.
References
2009
- (Liu, 2009) ⇒ Tie-Yan Liu. (2009). “Learning to Rank for Information Retrieval.” In: Foundations and Trends in Information Retrieval Journal, 3(3). [http://dx.doi.org/10.1561/1500000016 doi:10.1561/1500000016
- QUOTE: Learning to rank for Information Retrieval (IR) is a task to automatically construct a ranking model using training data, such that the model can sort new objects according to their degrees of relevance, preference, or importance. Many IR problems are by nature ranking problems, and many IR technologies can be potentially enhanced by using learning-to-rank techniques. …