Web sources are open, dynamic, and autonomous. They contain a great deal of incomplete, imprecise, and unqualified information. These issues result in unacceptable Web source quality. Evaluating and selecting high quality Web source/information is a key for the success of Web-based applications. In this paper, Web quality is modeled by using a Web quality model, WebQM. Fuzzy TOPSIS (FTOPSIS) is applied to evaluate and screen Web sources for advanced Web applications, such as data warehousing, OLAP, and data mining. In addition, an expert-average group evaluation strategy is combined with FTOPSIS to obtain more objective and more precise results. To illustrate our evaluation process, an example is discussed.