Fuzzy cognitive map approach to web-mining inference amplification

K Lee
2002 Expert systems with applications  
This paper is concerned with proposing the fuzzy cognitive map (FCM)-driven inference ampli®cation mechanism in the ®eld of webmining. As the recent advent of the Internet, most of the modern ®rms are now geared towards using the web technology in their daily as well as strategic activities. The web-mining technology provides them with unprecedented ability to analyze web-log data, which are seemingly full of useful information, but often lack of important and meaningful information. This
more » ... tes the need to develop an advanced inference mechanism extracting richer implication from the web-mining results. In this sense, we propose a new web-mining inference ampli®cation (WEMIA) mechanism using the inference logic of FCM. The association rule mining is what we adopt as the web-mining technique to prove the validity of the proposed WEMIA. The main recipe of the proposed WEMIA is the three-phased inference ampli®cation. The ®rst phase is to apply the association rule mining, and the second phase is to transform the association rules into FCM-driven causal knowledge bases. The third phase is dedicated to amplifying the inference by developing the causal knowledge-based inference equivalence property, which was derived from analyzing the inference mechanism of FCMs. With an illustrative web-log database, we suggest results proving the robustness of our proposed WEMIA mechanism. q
doi:10.1016/s0957-4174(01)00054-9 fatcat:lcvzil2nj5ehdivj7his4beegq