Modified Firefly Algorithm and Fuzzy C-Mean Clustering Based Semantic Information Retrieval

作者：M. Subramaniam, Kathirvel Ayyaswamy, E. Sabitha, H. A. Basha · 发表于：Journal of Web Engineering · 年份：2021 · DOI：10.13052/jwe1540-9589.2012 · 被引用次数：9 · 研究领域：Computer Science

As enormous volume of electronic data increased gradually, searching as well as retrieving essential info from the internet is extremely difficult task.  Normally, the Information Retrieval (IR) systems present info dependent upon the user’s query keywords. At present, it is insufficient as large volume of online data and it contains less precision as the system takes syntactic level search into consideration. Furthermore, numerous previous search engines utilize a variety of techniques for semantic based document extraction and the relevancy between the documents has been measured using page ranking methods. On the other hand, it contains certain problems with searching time.   With the intention of enhancing the query searching time, the research system implemented a Modified Firefly Algorithm (MFA) adapted with Intelligent Ontology and Latent Dirichlet Allocation based Information Retrieval (IOLDAIR) model. In this recommended methodology, the set of web documents, Face book comments and tweets are taken as dataset.  By means of utilizing Tokenization process, the dataset pre-processing is carried out. Strong ontology is built dependent upon a lot of info collected by means of referring via diverse websites. Find out the keywords as well as carry out semantic analysis with user query by utilizing ontology matching by means of jaccard similarity. The feature extraction is carried out dependent upon the semantic analysis. After that, by means of Modified Firefly Algorithm (M...