Purpose: To create a more effective algorithm for evaluating the publication activity of lecturers in comparison with the existing algorithms for the formation of the Hirsch index and ghp-index. Methods: The algorithm includes a mathematical description of all published works of the lecturer and their citations. The results of the scientific activity of the lecturer are reflected using the matrix form of recording statistical source data, consisting of citations for each published work of the author. The sequence of citations of publications in the matrix is determined by the non-increasing nature of citations in subsequent publications compared to the previous ones. The constructed matrix of the distribution of citations S by published works is rebuilt into a block matrix, which includes the following block matrices: H is the base matrix defining the Hirsch index; G is the matrix of significant publications located above the Hirsch matrix; P is the matrix of less-cited works of the lecturer; O is the zero matrix. The formed matrices have allowed the introduction of the following indices using Euclidean norms: h — Hirsch index, g — index of significant publications and p — index of intensive work. In turn, these indices have allowed to determine the following as Euclidean norms: gh — the index of basic significant publications, hp — the index of intensive work of a lecturer and a comprehensive ghp-index that takes into account all the published works of a lecturer and all their citations. The ghp-index has been improved by introducing weighting coefficients for its constituent indices. Results: The ratings of a team of 20 lecturers has been formed using a sample from the RSCI with the help of the Hirsch index and the A-ghp index. It is shown that the proposed algorithm is more effective in comparison with the Hirsch index and other introduced indexes. Practical significance: The conducted research has allowed to substantiate the possibility of using an improved comprehensive index to distribute the incentives of a team of lecturers in a differentiated and fair manner according to their rating. The algorithm aims to improve the scientific and methodological activities of lecturers by providing fair and accurate ranking of the members of their collectives.