Spam Filter Using Country and Language Frequency Scoring
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Solution Overview
Problem
Conventional spam-filtering technologies face challenges in effectively identifying junk emails across multiple languages and countries, particularly due to language-specific rules and sparse reputation information from foreign countries, which limits scalability and accuracy.
Innovation Solution
A system that detects junk emails by determining the country and language of an email message and comparing it to the recipient's communication habits, using a spam filter that assigns scores based on country and language frequencies to determine if a message is spam, improving scalability and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If language-specific spam-filtering rules are added for additional languages, then spam detection accuracy improves, but system complexity and scalability deteriorate
Solution Approach 1:
The patent applies universality by creating a single spam filtering system that handles multiple languages through language detection and adaptive rule application. Instead of maintaining separate filtering systems for each language, the system universally processes all languages by detecting the message language and applying appropriate rules dynamically, thereby improving scalability while maintaining detection accuracy across diverse languages including non-Roman alphabets
Solution Approach 2:
The system changes the parameter of rule application by making it dynamic rather than static. It detects the language parameter of incoming messages and adapts the filtering rules accordingly. This allows the same filtering infrastructure to handle multiple languages by changing which rules are applied based on the detected language, avoiding the need for permanently complex multi-language rule sets
2Adaptability or versatility
If reputation information from foreign countries is used to identify spam, then spam detection coverage improves, but reliability deteriorates due to sparse reputation data
Solution Approach 1:
The patent merges multiple information sources for spam detection: it combines language detection results, country of origin information, and reputation data into a unified filtering approach. By merging these factors, the system can compensate for sparse reputation information in foreign countries using complementary signals from language analysis and geographic origin, thereby maintaining reliability while expanding detection coverage to international spam
Solution Approach 2:
The system introduces language detection and country identification as intermediary steps between receiving international emails and applying reputation-based filtering. These intermediaries provide additional contextual information that bridges the gap caused by sparse reputation data in foreign countries, enabling more reliable spam identification by mediating between limited reputation information and the need for accurate filtering
3Productivity
If conventional spam-filtering rules are applied across multiple languages, then spam detection capability improves, but false positives increase due to language-specific characteristics
Solution Approach 1:
The patent applies local quality by tailoring the filtering rules to match the specific language characteristics of each incoming message. Instead of applying uniform rules to all languages, the system detects the language and applies rules specifically suited to that language's structure, character set, and common spam patterns. This localized approach reduces false positives caused by misinterpreting language-specific features while maintaining efficient spam filtering across diverse languages
Data Source
AI summary
Techniques to detect spam using language and a country of origin of an e-mail may include receiving an e-mail message for a recipient, detecting a country of origin for the e-mail message and detecting a language of the e-mail message. A technique may further include determining a country frequency with which the recipient communicates with the country of origin by e-mail, and a language frequency with which the recipient communicates in the language by e-mail. A technique may assign a first score to the message according to the country frequency, and a second score to the message according to the language frequency. The scores may used to determine whether the e-mail message is spam. Other embodiments are described and claimed.