Identify the Components of Artificial Intelligence in Iranian Databases
The purpose of this study was to identify the components of artificial intelligence in Iranian databases and the rate of its use in these databases.
This research is an applied and has done by documentary and survey method. The statistical population of this research includes 7 internal databases (Normags, Norlib, Magiran, Civilica, Irandoc, ISC and SID). Data collection tools were researcher-made notes and checklists and interviews with experts. Data analysis was performed using SPSS software.
The results showed that Irandoc database had the most and Civilica and Magiran databases had the least use of artificial intelligence components. It also has the most used components in databases and components. Components of "word Disambiguation in text", "name recognition and classification", "image translators", "description" "Image", "Speech to text conversion", "Text to speech conversion", "Audio translators" have had the least use in databases.
The results showed that the use of artificial intelligence components in Iranian databases can accelerate and facilitate the processes of processing, storing and retrieving resources in Iranian databases.
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