The Brief Bibliometric Analysis of the Topic: "Algorithms and Artificial Intelligence". WoS 2017-2019

The topic — "algorithms and artificial intelligence" is very broad, so only some aspects of bibliometric analysis were considered:

• Comparing the results of a general query and a request for publications related to industry; the results do not differ much; China is the main sponsor of this research domain, the next is US. "PEOPLES R CHINA"; "USA"; "IRAN"; "INDIA" — are the leaders in this field of research; "ISLAMIC AZAD UNIVERSITY" and "CHINESE ACADEMY OF SCIENCES" are at the top

• Verification of sustainability of analyzed results; the exclusion of a significant term (engineer*) from the request does not significantly affect the topic of publications in the resulting sample

• For better clustering results we have to build thesaurus and aggregate such words as: 'artificial-intelligence', 'artificial intelligence' and so on. In other words, we need to move from clustering to classification to get more sustainable results (only words in dictionary)

• 'Artificial intelligence', 'machine learning', 'neural-networks' — most used KW. convolutional neural networks — most used neural network. 'genetic algorithm', 'support vector machine', 'fuzzy logic' — most used algorithms. 'feature extraction' — essential part of any job. 'reinforcement learning'. 'firefly algorithm', ' random forest', 'ant colony optimization' — also worth of attention

• The most cited publications are the most focus on the topic