A survey on recommendation system for technical paper reviewer assignment

Recommendation System for Technical paper reviewer assignment is very important for many applications especially in the academic environment and industry. Previous work to build the expert finding system based on a paper title. Here we take a scenario of a conference where they need some experts who can review the paper for that we identify whether the reviewer is expert in that topic or domain to review the paper. To find the experts we are using DBLP dataset which contains the attributes such as author name, title, year, DOI, URL, publication name, etc. Based on the title and the URL we can easily get the abstract of the paper to identify the domain of a paper. Then we rank the experts based on his expertise in that domain. So we get the expert who can review the paper. Expert Finding System is a relatively new topic and is becoming popular in the literature. This paper surveys major issues and challenges related to Expert Finding System. It aims to classify and compare the strategies discussed in existing literature, as well as to provide useful information for current state and challenges of this topic and what actions need to be performed in order to come up with a better solution.