Semantic search is the aspirin to the headaches of keyword search in e-discovery, such as under-generation and over-generation of search results and translation errors.
Semantic search solves keyword search issues such as under-generation by looking at the meaning, as it does not matter how a concept is described. As semantic search focuses on an idea or meaning when attempting to match a static word that may have multiple meanings exactly, the overgeneration of search results is minimized.
In today’s global economy, e-discovery involves documents in multiple languages. Semantic search across languages minimizes errors from a translation by searching the text as written. While there may be some fuzziness, the meaning will be true. More significantly, because semantic search helps discover critical concepts and case-relevant phrases in different languages, it is possible to bootstrap them to create a starter glossary for machine translation and minimize labor. They also enable software to categorize the files automatically based on key phrases expressing similar ideas.
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