Data Localization Templates for Cross-Language Content Parsing
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Solution Overview
Problem
Social network services face challenges in making content accessible to users who speak different languages and are not familiar with the cultural context, as data posted in one language may not be understood by members from other cultures, leading to a tedious and time-consuming process to make it understandable.
Innovation Solution
The implementation of localization techniques that parse data from public feeds and form templates for each supported locale, allowing the data to be presented in a human language corresponding to the user's locale, using a canonicalization pattern for translation and cultural adaptation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If data is posted in one language, then the original poster does not need to translate, but users from other languages cannot understand the content
Solution Approach 1:
The system performs preliminary translation of content into multiple languages before the user consumes it. The translation service automatically translates the original content into target languages, so when users access the content, it is already available in their preferred language without requiring manual translation from the poster.
Solution Approach 2:
A translation service acts as an intermediary between the original content and the user. This intermediary component automatically translates content from the source language to the user's preferred language, enabling cross-language understanding without the original poster needing to know or care about the user's language preferences.
2Adaptability or versatility
If data is manually translated for each language, then language accessibility is improved, but the process becomes tedious and time-consuming
Solution Approach 1:
The translation service performs self-service by automatically translating content without human intervention. The system uses machine translation to autonomously convert content into multiple languages, eliminating the need for manual translation work and significantly reducing the time required to make content accessible to diverse language speakers.
Solution Approach 2:
The patent replaces the mechanical process of manual translation with an automated machine translation system. This substitution eliminates the tedious manual work and time consumption associated with human translation, while maintaining the ability to produce accurate translations for multiple languages.
3Adaptability or versatility
If content is localized for each locale, then cultural relevance is improved, but the complexity of the system increases
Solution Approach 1:
The translation service provides universal functionality by handling multiple languages and cultural contexts through a single unified system. Rather than requiring separate localization systems for each language or culture, this multi-functional service can translate and adapt content for any supported locale, reducing overall system complexity while maintaining high cultural relevance.
Data Source
AI summary
Localization techniques are described. In an implementation, data is parsed from a feed of data that is public and not localized. A template is formed from the data for each locale that is to be supported. The data that is localized for a particular locale is presented is based on a particular template for the particular locale.