Multilingual Semantic Similarity of Unstructured Enterprise Content

To communicate with their end users, businesses regularly produce written documents such as letters, notices, statements, etc. in various languages. A set of rules are usually used to ensure that information in these documents is 'correct' and consistent across languages and communication channels. However, with the increasing volume and variety of information being sent out to clients, it becomes difficult to preserve the semantics of client messages across vocabulary and language variations.

Multilingual Semantic Search Engine using Multilingual Semantic Similarity

Multiple situations require cross-lingual searching: lawyers reviewing litigation documents; intelligence analysts data mining open source data; and patent attorneys investigating technical documents. To imitate cross-lingual search, people use online translation platforms to find the equivalent terms laboriously and then re-execute the query multiple times in various languages. The commercial search industry hasn’t seen much demand for crosslingual search. Search is always monolingual and very English-centric.

Multilingual Semantic Similarity Engine

To communicate with their end users, businesses regularly produce written documents such as letters, notices, statements, etc.., in various languages. A set of rules are usually used to ensure that information in these documents is 'correct' and consistent across languages and communication channels. However, with the increasing volume and variety of information being sent out to clients, it becomes difficult to preserve the semantics of client messages across vocabulary and language variations.