In the scientific community, there is no single, objective, and precise metric for ranking the work of researchers based on their scientific merit. Most existing metrics are based on the number of publications associated with an author along with the number of citations received by those publications. However, there is no standard metric officially used to evaluate the researchers’ careers. In this paper, the Framework for Reputation Estimation of Scientific Authors (FRESA) to address this issue is depicted. It is a system able to estimate the reputation of a researcher focusing on the achieved publications. It calculates two indexes making use of the relevance and the novelty concepts in the scientific domain. The system can depict the scientific trajectories of the researchers through the proposed indexes to illustrate their evolution over time. FRESA uses web information sources and applies similarity measures, text mining techniques, and clustering algorithms to also rank and group the researchers. The presented work is experimental, rendering promising results.

在科学界，没有单一、客观和精确的衡量标准来根据研究人员的科学价值对他们的工作进行排名。大多数现有指标都是基于与作者相关的出版物数量以及这些出版物收到的引用数量。然而，并没有正式用于评估研究人员职业生涯的标准指标。本文描述了解决这一问题的科学作者声誉评估框架（FRESA ）。它是一个能够评估专注于所发表出版物的研究人员声誉的系统。它利用科学领域的相关性和新颖性概念来计算两个指数。该系统可以通过提出的指标来描绘研究人员的科学轨迹，以说明其随时间的演变。FRESA使用网络信息源并应用相似性度量、文本挖掘技术和聚类算法对研究人员进行排名和分组。所提出的工作是实验性的，呈现出有希望的结果。