What are the best practices for cross-language information retrieval in multilingual websites and apps?

1 Choose the right language detection method

The first step for CLIR is to identify the language of the user's query and the language of the available documents. There are different methods for language detection, such as using the browser settings, the IP address, the domain name, or the content itself. Each method has its advantages and disadvantages, depending on the accuracy, speed, and cost. For example, using the browser settings might be fast and easy, but it might not reflect the user's actual preference or location. Using the content itself might be more accurate, but it might require more computational resources and time. You should choose the method that best suits your needs and goals, and test it regularly for performance and reliability.

3 Apply relevant ranking and filtering criteria

The final step for CLIR is to rank and filter the translated documents according to their relevance and usefulness for the user's query. There are different ranking and filtering criteria, such as keywords, topics, categories, ratings, reviews, popularity, freshness, or location. Each criterion has its merits and limitations, depending on the context, purpose, and diversity of the information. For example, using keywords might be simple and straightforward, but it might also miss synonyms, variations, or nuances of meaning. Using topics or categories might be more comprehensive and organized, but it might also be vague or subjective. Using ratings, reviews, popularity, or freshness might be more dynamic and interactive, but it might also be biased or outdated. Using location might be more relevant and personalized, but it might also be restrictive or intrusive. You should apply the criteria that best reflect your content and audience, and optimize them regularly for relevance and quality.

4 Test and improve your CLIR system

CLIR is not a one-time task, but a continuous process of improvement and adaptation. You should test and improve your CLIR system regularly, using various methods and metrics. Some of the methods include user feedback, surveys, interviews, usability tests, or analytics. Some of the metrics include precision, recall, relevance, satisfaction, or engagement. You should use the methods and metrics that best capture your goals and outcomes, and use them to identify and address any issues or opportunities for improvement.

5 Follow the ethical and legal guidelines

CLIR is not only a technical issue, but also an ethical and legal one. You should follow the ethical and legal guidelines that apply to your domain, region, and audience, regarding issues such as privacy, security, copyright, consent, or fairness. You should respect the rights and preferences of your users and content providers, and avoid any actions that might harm or offend them. You should also be transparent and accountable for your CLIR system, and disclose any limitations or risks that might affect its performance or reliability.

6 Learn from the best examples

CLIR is not a new or isolated phenomenon, but a growing and evolving one. You should learn from the best examples of CLIR in multilingual websites and apps, and use them as inspiration or benchmark for your own CLIR system. Some of the best examples include Google Translate, which offers instant and comprehensive translation for over 100 languages; Wikipedia, which offers cross-language links and summaries for millions of articles; Netflix, which offers subtitles and dubbing for thousands of movies and shows; or Duolingo, which offers interactive and gamified language learning for dozens of languages. You should study how these examples implement and improve their CLIR systems, and how they address the challenges and opportunities of CLIR.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?