[go: up one dir, main page]

Zhang et al., 2003 - Google Patents

Filtering junk mail with a maximum entropy model

Zhang et al., 2003

View PDF
Document ID
5712107133418191666
Author
Zhang L
Yao T
Publication year
Publication venue
Proceeding of 20th international conference on computer processing of oriental languages (ICCPOL03)

External Links

Snippet

The task of junk mail filtering is to rule out unsolicited bulk e-mail (junk) automatically from a user's mail stream. Two classes of methods have been shown to be useful for classifying e- mail messages. The rule based method uses a set of heuristic rules to classify e-mail …
Continue reading at www.fon.hum.uva.nl (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/10Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
    • G06Q10/107Computer aided management of electronic mail
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00Data switching networks
    • H04L12/54Store-and-forward switching systems
    • H04L12/58Message switching systems, e.g. electronic mail systems
    • H04L12/585Message switching systems, e.g. electronic mail systems with filtering and selective blocking capabilities
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00Data switching networks
    • H04L12/54Store-and-forward switching systems
    • H04L12/58Message switching systems, e.g. electronic mail systems
    • H04L12/5885Message switching systems, e.g. electronic mail systems with provisions for tracking the progress of a message
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/20Handling natural language data
    • G06F17/27Automatic analysis, e.g. parsing
    • G06F17/2765Recognition
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00Data switching networks
    • H04L12/54Store-and-forward switching systems
    • H04L12/58Message switching systems, e.g. electronic mail systems
    • H04L12/5855Message switching systems, e.g. electronic mail systems with selective forwarding
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00Data switching networks
    • H04L12/54Store-and-forward switching systems
    • H04L12/58Message switching systems, e.g. electronic mail systems
    • H04L12/5825Message adaptation based on network or terminal capabilities
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/3061Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L51/00Arrangements for user-to-user messaging in packet-switching networks, e.g. e-mail or instant messages
    • H04L51/12Arrangements for user-to-user messaging in packet-switching networks, e.g. e-mail or instant messages with filtering and selective blocking capabilities
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L51/00Arrangements for user-to-user messaging in packet-switching networks, e.g. e-mail or instant messages
    • H04L51/14Arrangements for user-to-user messaging in packet-switching networks, e.g. e-mail or instant messages with selective forwarding
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L51/00Arrangements for user-to-user messaging in packet-switching networks, e.g. e-mail or instant messages
    • H04L51/06Message adaptation based on network or terminal capabilities
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L51/00Arrangements for user-to-user messaging in packet-switching networks, e.g. e-mail or instant messages
    • H04L51/28Details regarding addressing issues
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass

Similar Documents

Publication Publication Date Title
Zhang et al. Filtering junk mail with a maximum entropy model
US7930353B2 (en) Trees of classifiers for detecting email spam
EP1397768B1 (en) Method and apparatus for filtering email
US7949718B2 (en) Phonetic filtering of undesired email messages
Alurkar et al. A proposed data science approach for email spam classification using machine learning techniques
Peng et al. Enhancing the naive bayes spam filter through intelligent text modification detection
Firte et al. Spam detection filter using KNN algorithm and resampling
Govil et al. A machine learning based spam detection mechanism
KR20060043333A (en) Systems and methods for determining intent of data and responding to data based on intent
Ruskanda Study on the effect of preprocessing methods for spam email detection
Dada et al. Random forests machine learning technique for email spam filtering
Reddy et al. Classification of spam messages using random forest algorithm
Yang et al. Spam filtering using Association Rules and Naïve Bayes Classifier
Itskevitch Automatic hierarchical e-mail classification using association rules
Lan et al. Spam filtering based on preference ranking
Islam et al. Machine learning approaches for modeling spammer behavior
CN108710650B (en) A Topic Mining Method for Forum Texts
Glymin et al. Rough set approach to spam filter learning
Pera et al. SpamED: A spam E‐mail detection approach based on phrase similarity
Islam et al. An innovative analyser for email classification based on grey list analysis
Bellegarda et al. Automatic junk e-mail filtering based on latent content
Yaseen et al. An evaluation and analysis of static and adaptive Bayesian spam filters
Katirai et al. Filtering junk e-mail
Song et al. Intention extraction from text messages
Frederic Text Mining applied to SPAM detection