Artificial Intelligence is promoted as the solution to some of humanity’s hardest challenges. But AI and Machine Learning can be applied to the same problem in many ways, and different companies may even apply the same methods and get different results. So how can we meaningfully compare the results of machine learning tools from different providers?
In response to this challenge, the R&D team at UNSILO has just released an updated white paper which presents a method for quantitative comparison, based on well defined and simple qualitative criteria for extracted concepts, and then applies this method to compare the quality of the UNSILO concept extraction to similar services from Google, Microsoft, IBM, and the recently launched Keyphrase Extraction API from Amazon Comprehend.
The test was performed using a random selection of papers from four different scientific domains, and show that the UNSILO concept extraction has the best performance of all the evaluated services, scoring an amazing 2.5 times higher than the average competing services across all domains.
The results show that UNSILO provides consistent high-quality output with little or no noise, across very diverse domains. Compared to the incumbents, UNSILO provides more precise concepts, and is able to detect key concepts in unknown domains without the use of an underlying ontology.
Follow the link below to download the white paper, and have a look at the underlying data on page two for yourself.