Keywords
Database, artificial intelligence, hybrid models, auto-system generation, performance, search engine, knowledge graph, recommender systems, AI models
Disciplines
Engineering
Abstract
In recent years, the world of AI has tremendously increased in size and depth. Both new and old researchers are facing the problem of fast emerging AI researches, models and services. One needs to continuously read complete papers to understand the idea behind any novel research. This work presents a novel AI service that removes the burdens of long text reading and uncategorized search. It consists of a website that categorizes all the AI researches in a well-designed database. The users just have to select the models they are interested in, and the website will return a table containing the technical data in addition to a graph that shows visual relationships between the AI models, features and datasets. Future work will emphasize on developing the tool by applying NLP in two directions: one on the search box to retrieve the main keyword to search for, and the other on research papers to automatically extract the data into the website categorized database.
Author ORCID Identifier
Imane Haidar- https://orcid.org/0009-0000-0508-2963
Ziad Doughan- https://orcid.org/0000-0002-7566-7710
Ali M. Haidar- https://orcid.org/0000-0001-8065-3658
Recommended Citation
Haidar, Imane; Doughan, Ziad; and Haidar, Ali M. Prof.
(2023)
"A NOVEL SPECIALIZED SEARCH ENGINE FOR AI-MODELS AND THEIR COMPARISON,"
BAU Journal - Creative Sustainable Development: Vol. 4:
Iss.
2, Article 2.
DOI: https://doi.org/10.54729/2789-8334.1099
ISSN
2789-8334