Main Article Content
The internet plays a key role in life through the massive data that it provides. Currently, managing data and finding information on the internet is inaccurate because it depends on the form of the word rather than its meaning. Data representation and access are important factors when it comes to Information Retrieval (IR). In order to overcome the problem of document similarity, there are various similarity measurements in place that function according to weight, indexing and matching. Ontology is a data management infrastructure that gives precedence to the meaning of a word, the relationship between words and the domain of knowledge.
This paper presents a semantic system proposal based on a particular field of knowledge (time nouns) and relies on semantic input by indexing the search engine using a Vector Space Model (VSM). The aim of this work is to improve the retrieved semantic information by constructing a query based on the matching and similarity between the query words in the system. This paper builds upon previous work carried out in the same area . The system was evaluated by using the similarity, average precision and recall of the experiments' results.