International Journal of Computer Science Issues

More than a traditional journal...

The current information retrieval mechanisms are based on models such as Boolean model, extended Boolean model, vector space model, and probabilistic model and language models. However, these models fall short of expectations, leading to misunderstanding of the user query and therefore the information retrieved fail to meet user expectations. In this paper, a novel search technique is proposed as the possible solution to the problems inherent in the current information retrieval models. To achieve this objective, an experimental research design was utilized. This new technique is based on the concept of N-gram coupled with a conceptual search in which information is searched based on meaning instead of matching of keywords. Thereafter, N-grams are employed to tokenize and display the retrieved information. To validate the proposed approach, a number of experimentations were carried out based on the current search criteria as well as the N-gram based semantic search. The results obtained demonstrated that the proposed information retrieval technique outperformed the current models in terms of precision, recall and F-measure. As such, this model proves significant in the information retrieval process as it accomplishes search by meaning instead of keyword based searching.