| Abstrakt: |
Presently, information retrieval can be accomplished simply and rapidly with the use of search engines. This allows users to specify the search criteria as well as specific keywords to obtain the required results. Additionally, an index of search engines has to be updated on most recent information as it is constantly changed over time. Particularly, information retrieval results as documents are typically too extensive, which affect on accessibility of the required results for searchers. Consequently, a similarity measurement between keywords and index terms is essentially performed to facilitate searchers in accessing the required results promptly. Thus, this paper proposed the similarity measurement method between words by deploying Jaccard Coefficient. Technically, we developed a measure of similarity Jaccard with Prolog programming language to compare similarity between sets of data. Furthermore, the performance of this proposed similarity measurement method was accomplished by employing precision, recall, and F-measure. Precisely, the test results demonstrated the awareness of advantage and disadvantages of the measurement which were adapted and applied to a search for meaning by using Jaccard similarity coefficient. [ABSTRACT FROM AUTHOR] |
