Classification of Authors for a Recommendation Process Integrated to a Scientific Meta-Search Engine

Abstract

The search for scientific production on the web has become a challenge, both in terms of volume, variety and updating speed. It requires tools that help the user to obtain relevant results when executing a query. Within these tools, this team has developed a specific meta-search engine for the area of computer science. In its evolution, it is intended to include recommendations from authors for each of its users’ queries. The generation of such recommendations requires a method capable of classifying the authors in order to define their inclusion and position in a list of suggestions for the end-user. This paper presents a method that fulfills this objective, after being evaluated and having obtained results that allow to propose its inclusion in later development of the recommendation system.