A survey on Learning to Rank (LETOR) approaches in information retrieval

In Recent years, the application of machine learning approaches to conventional IR system evolve a new dimension in the field. The emphasis is now shifted from simply retrieving a set of documents to rank them also for a given query in terms of user's need. The researcher's task is not only to retrieve the documents from the corpus but also to rank them in order of their relevance to the user's requirement. To improve the system's performance is now the hot area of research. 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.