Schema matching is a critical problem in many applications where the main goal is to match attributes coming from heterogeneous sources. In this paper, we propose PROCLAIM (PROfile-based Cluster-Labeling for AttrIbute Matching), an automatic, unsupervised clustering-based approach to match attributes of a large number of heterogeneous sources. We define the concept of attribute profile to characterize the main properties of an attribute using: (i) the statistical distribution and the dimension of the attribute's values, (ii) the name and textual descriptions related to the attribute. The attribute matchings produced by PROCLAIM give the best representation of heterogeneous sources thanks to the cluster-labeling function we defined. We evaluate PROCLAIM on 45,000 different data sources coming from oil and gas authority open data website3. The results we obtain are promising and validate our approach.

Effectiveness of websites is largely dependent on the quality of the website. The biggest share of the quality`s new concept is that the technical aspects of products and services combines with customers usage and understanding. Therefore websites evaluation based on the maximum usage and perception of the customers is considered an important issue to announce to the related organizations the success of website from customers' views. This customer relationship need a kind of management that first step of that for future decision needs knowledge about the websites features, customer insight and the position of websites among the competitors. One of the available media is the online news websites which their success is highly dependent on the relationship of their users. In this article achieving the information of websites is automatic and without the intervention of human so that the instant evaluation could be possible and used method is TOPSIS combined with information entropy to rank 791 news website which have most visitors of the Iranian users based on Alexa ranking report.