Non - crisp Clustering Web Visitors by Fast , Convergent and Robust Algorithms on
نویسنده
چکیده
The algorithms proposed to date for categorizing WEB-visitors are all of quadratic time complexity (they essentially require computing the dissimilarity between all pairs of paths). These clustering eeorts, although not scalable, have demonstrated the extensive beneets and sophisticated applications emerging from identifying groups of visitors to a web site. We provide a sub-quadratic clustering algorithms for generic dissimilarity in paths. Our algorithms are robust because they use medians rather than means as estimators of location, and the resulting representative of a cluster is actually a path in the item set. We demonstrate mathematically that our algorithms converge. The methods proposed generalize approaches that allow a data item to have a degree of membership in a cluster. Because our algorithm is generic to both, fuzzy membership approaches and probabilistic approaches for partial membership, we simply name it non-crisp clustering.
منابع مشابه
A density based clustering approach to distinguish between web robot and human requests to a web server
Today world's dependence on the Internet and the emerging of Web 2.0 applications is significantly increasing the requirement of web robots crawling the sites to support services and technologies. Regardless of the advantages of robots, they may occupy the bandwidth and reduce the performance of web servers. Despite a variety of researches, there is no accurate method for classifying huge data ...
متن کاملInterval set clustering of web users using modified Kohonen self-organizing maps based on the properties of rough sets
Web usage mining involves application of data mining techniques to discover usage patterns from the web data. Clustering is one of the important functions in web usage mining. The likelihood of bad or incomplete web usage data is higher than the conventional applications. The clusters and associations in web usage mining do not necessarily have crisp boundaries. Researchers have studied the pos...
متن کاملCombination of Cluster Method for Segmentation of Web Visitors
Clustering is one of the important part in web usage miningfor the purpose of segmenting visitors. This action is very important for web personalization orweb modification. In this paper, we perform clustering of the web visitors using a combination of methods of hierarchical and non-hierarchical clustering toward web log data. Hierarchical clustering method used to determine the number of clus...
متن کاملFuzzy Graph Clustering based on Non-Euclidean Relational Fuzzy c-Means
Graph clustering is a very popular research field with numerous practical applications. Here we focus on finding fuzzy clusters of nodes in unweighted, undirected, and irreflexive graphs. We introduce three new algorithms for fuzzy graph clustering (Newman–Girvan NERFCM, Small World NERFCM, Signal NERFCM). Each of these three new algorithms uses a popular algorithm for crisp graph clustering an...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2001