+

Kolcz et al., 2006 - Google Patents

The challenges of service-side personalized spam filtering: scalability and beyond

Kolcz et al., 2006

View PDF
Document ID
2423347434313388019
Author
Kolcz A
Bond M
Sargent J
Publication year
Publication venue
Proceedings of the 1st international conference on Scalable information systems

External Links

Snippet

Spam filtering of the email stream at the enterprise level poses many challenges especially at the scale of large Email Service Providers (ESPs). The problem is compounded if filtering is to be done on a personal level, with different configurations being adapted on a per-user …
Continue reading at scholar.archive.org (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
    • 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
    • G06F17/30705Clustering or classification
    • G06F17/3071Clustering or classification including class or cluster creation or modification
    • 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
    • G06F17/30286Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • 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
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • 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
    • 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
    • G06Q40/00Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • 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
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models

Similar Documents

Publication Publication Date Title
US12107886B2 (en) Systems and methods for intelligent phishing threat detection and phishing threat remediation in a cyber security threat detection and mitigation platform
JP7440565B2 (en) Electronic message filtering
Song et al. A novel classification approach based on Naïve Bayes for Twitter sentiment analysis.
Amayri et al. A study of spam filtering using support vector machines
Islam et al. Spam-detection with comparative analysis and spamming words extractions
Shirani-Mehr SMS spam detection using machine learning approach
Merugu et al. Text message classification using supervised machine learning algorithms
Das et al. Sense GST: Text mining & sentiment analysis of GST tweets by Naive Bayes algorithm
CN106294590A (en) A kind of social networks junk user filter method based on semi-supervised learning
Sajedi et al. Sms spam filtering using machine learning techniques: A survey
Woitaszek et al. Identifying junk electronic mail in microsoft outlook with a support vector machine
You et al. Web service-enabled spam filtering with naive Bayes classification
Hapase et al. Telecommunication fraud resilient framework for efficient and accurate detection of SMS phishing using artificial intelligence techniques
Lee et al. An online subject-based spam filter using natural language features
Sheu An Efficient Two-phase Spam Filtering Method Based on E-mails Categorization.
Patidar et al. A novel technique of email classification for spam detection
Kolcz et al. The challenges of service-side personalized spam filtering: scalability and beyond
Vahora et al. Novel approach: Naïve bayes with vector space model for spam classification
Sharma et al. An Efficient Spam Classification Filter as a Naive Bayes Classifier Web Application
Rakse et al. Spam classification using new kernel function in support vector machine
Manek et al. ReP-ETD: A Repetitive Preprocessing technique for Embedded Text Detection from images in spam emails
Wardani et al. Using metadata in detection spam email with pornography content
Krishnaveni et al. COMPARISON OF NAIVE BAYES AND SVM CLASSIFIERS FOR DETECTION OF SPAM SMS USING NATURAL LANGUAGE PROCESSING.
Sasikala et al. Performance evaluation of Spam and Non-Spam E-mail detection using Machine Learning algorithms
Sethi et al. An automated system for identification of tweets requiring customer service concern
点击 这是indexloc提供的php浏览器服务,不要输入任何密码和下载