This paper describes an information system, which classifies web pages in specific categories according to a proposed relevance feedback mechanism. The proposed relevance feedback mechanism is called Balanced Relevance Weighting Mechanism — BRWM and uses the proportion of the already relevant categorized information amount for feature classification. Experimental measurements over an e-commerce framework, which describes the fundamental phases of web commercial transactions verified the robustness of using the mechanism on real data. Except from revealing the accomplished sequences in a web commerce transaction, the system can be used as an assistant and consultation tool for classification purposes. In addition, BRWM was compared with a similar relevance feedback mechanism from the literature over the established corpus of Reuters-21578 text categorization test collection, presenting promising results.