In Part 3 of a series on optimizing searches of Chinese, Japanese, and Korean text using Elasticsearch 6.2, Kiju Kim introduces a language detection technique to enhance efficiency and conserve storage space. By employing an ingest plugin for language detection, the method detects the language of the text and assigns it to a specific language field using the langdetect processor, which allows the original text to be copied into language-specific fields for analysis. This approach contrasts with the previously discussed multi-fields method, which stores text in multiple fields regardless of its language, potentially wasting resources. The language detection pipeline is demonstrated using content from the 2018 PyeongChang Olympic Games, showcasing how language-specific analyzers like kuromoji, smartcn, and openkoreantext-analyzer filter and process text. Although indexing with a language detector or multi-fields takes slightly more time than using a single field, the language detector method provides improved search results and storage efficiency, demonstrating a significant advantage over the multi-fields approach.