Feature selection has been an important issue in machine learning and data mining, and is
unavoidable when confronting with high‐dimensional data. With the advent of multilabel …

Personal and business users prefer to use e-mail as one of the crucial sources of
communication. The usage and importance of e-mails continuously grow despite the …

The accuracy of a 3D reconstruction using laser scanners is significantly determined by the
detection of the laser stripe. Since the energy pattern of such a stripe corresponds to a …

Spamming and phishing are two types of emailing that are annoying and unwanted, differing
by the potential threat and impact to the user. Automated classification of these categories …

Purpose This research study proposes a feature-centric spam email detection model
(FSEDM) based on content, sentiment, semantic, user and spam-lexicon features set. The …

Feature selection has received considerable attention over the past decade. However, it is
continuously challenged by new emerging issues. Semi-supervised multi-label learning is …

Spamming and phishing are two types of emailing that are annoying and unwanted, differing
by the potential threat and impact to the user. Automated classification of these categories …

Traditional single-label classification in machine learning and pattern classification fields is
concerned with learning from a set of examples that are associated with a single label from a …

Semantics based multi-layered networks for spam email detection - NASA/ADS Now on home
page ads icon ads Enable full ADS view NASA/ADS Semantics based multi-layered networks …

Nowadays data mining algorithms are successfully applying to analyze the real data in our
life to provide useful suggestion. Since some available real data is multi-valued and multi …