Spread Clustering based on Associated Keywords Extraction for an Efficient Knowledge Searching

An efficient searching system is needed to offer the exact result of diverse information to user in an enormous amount of web information. Due to this reason, it is important to extract and analysis of user requirements in the distributed information environment. The conventional searching method used the only keyword for the web searching. However, this paper analyzes query process of users approach and searching log data to the result documents. Thereafter, it extracts document lists based on subject words. Due to this reason, this paper proposes a method which provides keywords closely and mutually related to certain subject words for an efficient searching. In addition, it provides a clustering method that finds most relevant itemsets among extracted itemsets of related keywords. Unlike the conventional searching method which searched for information by a representative word, this proposed method in this paper is much more efficient and exact. The performance of the proposed algorithm is analyzed by a series of experiments to identify its various characteristic.