## 3 Results  
As a result of the keyword search of the three reference areas in the Scopus database, a total of 970 publications was obtained, whose temporal distribution can be seen in Figure 1. Starting in 2000, a considerable number of documents have been published, reaching a maximum of 91 documents in 2008, with the minimum value in 2014 with 16 documents. This has increased again in recent years, exceeding 50 articles in 2020 and 2021. It is possible to affirm, therefore, that the application of artificial intelligence in the field of innovation project management has been an area of great interest in recent years. The main sources with the highest number of publications, such as Lecture Notes in Computer Science and the International Journal of Project Management, are shown in Table 2.  
Figure 2 presents a two-dimensional bibliometric map resulting from the analysis of the 970 publications obtained in the initial query. As explained in the Materials and Methods section, VOSviewer software only shows on the map those keywords that exceed a certain frequency threshold. This threshold was adjusted so that the number of resulting terms was not too high in a way that made it difficult to interpret the groups obtained. In this case, four clusters were identified, and, as expected, given the keywords used in the query, terms such as project management, artificial intelligence, and knowledge-based systems appeared highlighted, that is, with a high frequency of occurrence. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Stakeholders** & **Team** & **Life Cycle** & **Planning** \\ \hline stakeholders & team & life cycle & planning \\ suppliers & group & phase & schedule \\ customers & leader & predictive & duration \\ end users & member & adaptive & effort \\ regulatory bodies & individual & & dependency \\  & motivation & & \\  & communication & & \\  & collaboration & & \\  & skill & & \\  & conflict & & \\ \hline
**Work** & **Delivery** & **Measurement** & **Uncertainty** \\ \hline work & delivery & measurement & risk \\ resource & scope & metric & threat \\ bid & quality & baseline & opportunity \\ contract & requirement & indicator & uncertainty \\ cost & change & efficiency & contingency \\  & & performance & \\  & & forecast & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Keywords for each project performance domain. Therefore, the interest of the co-word analysis is in the rest of the terms that appear in each cluster: \begin{table}
\begin{tabular}{c c c} \hline \hline
**Source** & **ISSN** & **Number of Documents** \\ \hline Lecture Notes in Computer & 0302-9743 & 41 \\ Science & & \\ International Journal of & 0263-7863 & 19 \\ Project Management & 1877-0509 & 18 \\ Procedia Computer Science & 1877-0509 & 18 \\ Advances in Intelligent & 2194-5357 & 15 \\ Systems and Computing & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Main sources of published documents. Figure 1: Documents published per year (Scopus). Figure 2: Clusters identified by VOSviewer. * Cluster 1, colored in red in the figure, is defined by 14 keywords, mainly related to software (computer software, software design, and software engineering), risk (risk assessment and risk management), and machine learning as the most outstanding aspects;
* Cluster 2, presented in green and defined by 11 terms, is mainly related to the management of knowledge and information (knowledge acquisition, knowledge management, knowledge-based systems, and information technology);
* Cluster 3, colored in blue and defined by 9 terms, includes terms such as decision-support systems, decision making, problem solving, and product development;
* Cluster 4, in yellow in Figure 2, is made up of only 2 terms, engineering research and research projects. The analyses carried out in the specific areas of project management defined by the PMI are described below. The number of publications related to each of these domains is reflected in Figure 3 and can provide an idea of which areas are being worked on more intensively.