Semantic search enables searching for meanings represented as vectors, allowing for broader searches even when text keywords do not match exactly. Additionally, because it is not limited to text, semantic search can target images, videos, and audio data as well.
Applications that can benefit from the strengths of semantic search include:
- Forum Search, Enterprise Search, Knowledge Management: These applications involve highly specialized documents that inherently carry strong semantic meanings.
- FAQs, Manuals: Similarly, these documents are highly specialized and carry strong semantic meanings. However, the searchers (such as product users, likely to be external) are not experts, which creates a large vocabulary gap. Therefore, semantic search has an advantage because keyword searches would yield extremely low recall rates.
- Multimodal-Search: Includes image-to-image, text-to-image, and cross-language (e.g., Japanese and English) searches. Since the search is based on meanings, it is possible to search effectively even if the query and the documents are of different object types.
- Inquiry-Based Learning and Research & Development: Educational resources (dictionaries, encyclopedias, textbooks) and highly specialized papers can easily implement associative searches based on semantic meanings. This is suitable for exploratory searches typical in inquiry-based learning and R&D.
