Chameleon Clustering Algorithm with Semantic Analysis Algorithm for Efficient Web Usage Mining

A Review on Clustering Techniques: Creating Better User Experience for Online Roadshow

“…Pransanth et al [39] proposed a system that can discover the user's frequent search pattern by clustering the weblog and performing semantic analysis. In addition, ref.…”

“…In addition, ref. [40] is a continuation of [39] by adding the recommendation rules into the CHAMELEON clustering. These recommendation rules help to retrieve the best access pages from the user's frequent pattern access history.…”

“…These recommendation rules help to retrieve the best access pages from the user's frequent pattern access history. When the performances of the proposed algorithms of [39,40] are compared, the CHAMELEON clustering with semantic analysis and recommendation rules approach has better results. This might be a better approach for a recommender system in suggesting web pages to users as it considers two factors: the semantics of information and the recommendation rules.…”

“…External criteria measure the quality of the clusters based on the ground truth in three ways. The first type is to perform clustering on the weblog and calculate the clustering quality with the actual class label by using any of the evaluation metrics [22,29,30,34,36,[39][40][41][42]48,58,61,64,71]. In the second type, the dataset is first split into training and testing datasets.…”

“…DBSCAN [48], k-medoids [33], CHAMELEON [39], k-means [23] Web queries categorization Classifying a web search query to one or more categories based on the topics enables users to easily find their interested topic. Users will feel more comfortable and in control when navigating the website.…”