The scientific literature review is a critical account of the main papers in a particular subject area or topic. In this way, the authors surveys the literature and present the relevant articles in an organized way by publication date and evolution of the research topic, which gives an overview of the state of the art in a subject. Through these relevant papers it is also possible to identify the most expert authors in the area or in certain papers, thus providing a solution to the problem of finding potential expert candidates. The main challenge of making a literature review is to identify the most relevant articles that reflect the evolution of the different research topics. In this thesis, we propose a visual collaborative approach that uses graphs to recommend important references. In addition, we introduce the task of searching and ranking authors given a target paper using relevant citation paths. From a ranking of references, the value of the author s expertise is calculated. A methodology is proposed in order to build and update the citation graph in a collaborative way with the expert s votes.