This research is related to the field of biometrics. The biometrics research consists of fingerprint scans, retina scans, voiceprint analyses, and so on [1]. Although an electronic signature (eSignature) does not actually come from human, it comes from an indirect tissue (i.e. handwriting) of a human. For instance, a handwritten signature will be collected from a cardholder when filling out the application form of credit card and formularized from a normal signature to an electronic signature. This eSignature will then be transmitted and stored into XML document in a data center. We will extract the eSignature that is a group of numbers from the database. This group of numbers is a factor in preceding the Online Analytical Mining (OLAM) [2]. We use the Internet as a network channel. We will also use the XML-RPC [6] to implement the active rules and apply OLAM to verify incoming eSignatures. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Fong, J., Cheung, S. K., & Kwan, I. (2003). eSignature verification on web using statistical mining approach. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2642, 293–300. https://doi.org/10.1007/3-540-36901-5_30
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