Özet:

Abstract Today, there are numerous methods of finding information online: radio, TV, and the internet all provide answers. However, the Internet stands out as being particularly helpful; users can search by typing in questions related to any subject area they wish. Results appear as links to various documents available on the internet, some of which may not even be relevant due to the vast amount of material. Search engines reliant solely on keywords are incapable of making sense of raw data, making it time-consuming and costly to extract critical pieces from an immense collection of web pages. Due to these deficiencies, several concepts were born, such as the Semantic Web (SW) and ontologies. SW serves as an excellent gateway for retrieving key information through various Information Retrieval (IR) techniques. IR algorithms are too simplistic to extract the semantic content from texts. IR, SW, and ontologies can all be used interchangeably, although all three have some connection. The SW can be achieved through IR, while indexing can lead to its creation on the web. The SW is also created through ontologies. Ontologies can be used together with the intelligent approaches to produce web content, which is then marked up using SW Documents. Ontology is the backbone of any software; therefore, the SW becomes simpler to comprehend. Ontology development is the process of creating and refining an ontology over time. This paper investigates various approaches, methodologies, and datasets used to address challenges in information retrieval, including corpus preparation, annotation techniques, query expansion, semantic reasoning, content alignment, and ontology-based retrieval systems.

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