Information Retrieval (IR) is a field that concerns the structure, memory, analysis, and access
to pieces of information. It has a wide application in various areas like search engines, communication
systems, information filtering, medical search, etc., and helps design efficient and secure applications.
This area has been a surge of research from the last few years due to data mining's unparalleled success,
deep learning in computer vision, blockchain technology, etc. Core models, performance evaluation
techniques, IR system applications, and its role in blockchain technology have been proposed in this
literature, calling the need for a broad survey to focus the research in this promising area. This paper
fills the space by surveying the state of art approaches with deep learning models, query expansion
techniques used, and the use of private information retrieval in blockchain technology. This survey
paper includes different IR models like boolean model, vector space model, probabilistic model,
language model, N-gram model, fuzzy model, Latent Semantic Indexing (LSI) Model, Bayesian
network, Evolutionary algorithm-based models and Machine Learning based models. Applications of IR
systems along with different datasets are also included to provide further research in this field.