Pattern mining technique derived ant colony optimization for document information retrieval

Abstract

Information retrieval is defining a structured knowledge from unstructured resource that satisfies the information needed from large collection of resources. document information retrieval (DIR) confines the resources in terms of documents where the term resource implicate text, audio, video, image and so on. In this paper, an advanced analysis in the field of Data Mining with Evolutionary concept is addressed namely DIR using ant colony optimization. The model consists of fuzzy C-means clustering and frequency set mining procedures to extract the information from the documents as pre-processing segments in the first phase. In the second phase, ant colony optimization is used to explore the document space in an intelligent manner to extract knowledge from it. Initially the documents are pre-processed, and a cluster is formed among the documents based on the pre-processed information. Later ants are used to explore each cluster in an intensive manner. The proposed model is evaluated with three different range of which can be classified as small, medium, and large sizes of documents from online sources. The results prove the significance of the proposed model when compared with the existing algorithms.