Short Message Age Classification via Linguistic Feature Extraction
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Solution Overview
Problem
Current data mining techniques are inadequate for analyzing short messages due to their brevity, making it difficult to extract useful user information such as age from large volumes of text data generated via social networking services.
Innovation Solution
A classification system that determines keyword feature information from short messages using features like vowel/consonant ratio, capitalization, emoticon usage, punctuation, texting slang, and keyword frequency, employing classifiers like Naïve Bayesian and maximum entropy classifiers to estimate user age.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If current data mining techniques are used to analyze short messages, then the analysis can be performed using existing tools, but the brevity of short messages makes it difficult to extract useful user information
Solution Approach 1:
The patent changes the parameters used for analysis from traditional text mining approaches to linguistic features specific to short messages. It extracts features such as vowel/consonant ratios, capitalization patterns, emoticon usage, punctuation styles, texting slang, and keyword frequency - these are parameter changes tailored to the brevity constraint of short messages, enabling effective user information extraction despite the limited text length
2Quantity of substance
If the volume of short messages is increased to improve data quantity, then more data is available for analysis, but the brevity of each message makes information extraction more difficult
Solution Approach 1:
The patent extracts specific linguistic features from short messages that are most indicative of user demographics. By taking out and analyzing specific features such as vowel/consonant ratios, capitalization patterns, emoticon usage, punctuation styles, texting slang, and keyword frequency, the system can effectively extract user information even from the limited text content of short messages, preventing information loss despite the brevity constraint
Data Source
AI summary
Systems and methods for short message age classification in accordance with embodiments of the invention are disclosed. In one embodiment of the invention, classifying messages using a classifier includes determining keyword feature information for a message using the classifier, classifying the determined feature information using the classifier, and estimating user age using the classifier.