Information Retrieval using Machine learning for Ranking: A Review

Abstract

Abstract The Ranking is one of the big issues in various information retrieval applications (IR). Various approaches to machine learning with various ranking applications have new dimensions in the field of IR. Most work focuses on the various strategies for enhancing the efficiency of the information retrieval system as a result of how related questions and documents also provide a ranking for successful retrieval. By using a machine learning approach, learning to rank is a frequently used ranking mechanism with the purpose of organizing the documents of different types in a specific order consistent with their ranking. An attempt has been made in this paper to position some of the most widely used algorithms in the community. It provides a survey of the methods used to rank the documents collected and their assessment strategies.