Employing artificial intelligence techniques in documents & Records indexing, content analysis and information retrieval: Zinki platform as a model.

The study dealt with important and vital subject; it is indexing of records, its definition, types, importance, features, methods, and stages, aiming to clarify the possibility of employing artificial intelligence techniques in indexing historical and digitally generated records. It presented a range of AI-supported techniques and tools used in the indexing process, and the use of these tools in indexing significant terms and semantic indexing, with the aim of improving the quality and efficiency of information retrieval, and their ability to convert their texts into searchable digital texts,, that indexes both printed and handwritten texts, whether old or modern, and searches them with high efficiency. The study adopted a descriptive methodology and case study for models of AI-supported global platforms, using content analysis tools to analyze the content of the study sample platforms, focusing on the Zinki platform and the Sabr system emerging from it,. The study concluded with a set of results, the most important of which is the possibility of using artificial intelligence techniques in indexing electronic and digital records written by machines. It also identified the limitations of artificial intelligence techniques in indexing historical records and manuscripts written by hand . The study recommended that institutions preserving documentary heritage should focus on the digitization process of the preserved documentary heritage, in preparation for using artificial intelligence techniques in records indexing. It also suggested collaboration between records and archive specialists and specialists in computer technology and artificial intelligence in indexing records,