Ranking is one of the problems in Information Retrieval (IR). Machine learning techniques and its various applications in ranking give new dimension in field of IR. Most of the work is focussing the how to improve IR system performance with degree of relevance between query and documents also provide ranking for efficient retrieval. Learning-to-rank is one of the learning frameworks in machine learning and it aims to organize the objects in a particular order according to their preference, relevance or ranking. In this paper, an attempt has been made to put some of most commonly used algorithms in the community. It presents a survey on the approaches used to rank the retrieved documents and their evaluation strategies.
Volume 11 | 08-Special Issue
Pages: 3134-3142