A Short Introduction to Learning to Rank

A Short Introduction to Learning to Rank. Li, H. IEICE TRANSACTIONS on Information and Systems, E94-D(10):1854–1862, October, 2011. Publisher: The Institute of Electronics, Information and Communication Engineers

Paper abstract bibtex

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 and significant progress has been made [1],[2]. This short paper gives an introduction to learning to rank, and it specifically explains the fundamental problems, existing approaches, and future work of learning to rank. Several learning to rank methods using SVM techniques are described in details.

@article{li_short_2011,
	title = {A {Short} {Introduction} to {Learning} to {Rank}},
	volume = {E94-D},
	issn = {1745-1361, 0916-8532},
	url = {https://search.ieice.org/bin/summary.php?id=e94-d_10_1854&category=D&year=2011&lang=E&abst=},
	abstract = {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 and significant progress has been made [1],[2]. This short paper gives an introduction to learning to rank, and it specifically explains the fundamental problems, existing approaches, and future work of learning to rank. Several learning to rank methods using SVM techniques are described in details.},
	number = {10},
	urldate = {2021-10-15},
	journal = {IEICE TRANSACTIONS on Information and Systems},
	author = {Li, Hang},
	month = oct,
	year = {2011},
	note = {Publisher: The Institute of Electronics, Information and Communication Engineers},
	pages = {1854--1862},
}

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