چكيده به لاتين
Today, many systems in the country are providing various services to the government and the public, which brings numerous benefits, such as saving time, reducing costs and paperwork, increasing access to the government, and enhancing organizational transparency. However, each of these systems has been developed by specific organizations and teams within particular domains, making pairwise integration of these e-government systems costly and time-consuming.
The proposed solution for this issue is a semantic interoperability framework that acts as a mediator between all systems, facilitating the translation of communication at the level of exchanged messages. Such a framework does not concern itself with the network, the method of message transmission, or their format but focuses solely on the content of the messages. Essentially, this framework operates at the presentation layer of the OSI model.
These frameworks typically require a system for search and discovery within existing domains to enable the creation of new domains and the translation of messages for both humans and machines. It seems that current systems lack the ability to identify synonymous, similar, or related words within a semantic domain, which complicates the work for domain experts and limits automation capabilities.
In this thesis, a search engine with such capabilities will be developed. The outcome of this research will be a search engine that provides semantic search functionality to developers of an interoperability framework. This solution involves expanding the query using several approaches, leading to obtaining appropriate results, even if the user does not search for the correct word. On the other hand, the results must be limited in order to increase the systemʹs accuracy and prevent the user from facing a flood of less relevant results. This is achieved by filtering the results. Finally, the results should be sorted by relevance and their likelihood of being useful to the user, which we accomplish by combining several methods such as using a knowledge graph and taxonomies. A comparison of Semsearch, which is the outcome of this thesis, with similar search engines shows its significant superiority, especially in helping the user retrieve relevant phrases and score the results.
