Automated Semantic Enrichment
Semantically tagging content, efficiently
Nstein’s solutions automatically crawl and analyze text archives, identifying key concepts, people, categories, context, sentiment, and entities and subsequently encasing content in a layer of rich, semantic metadata. The direct benefits of this process are twofold: (1) It liberates IT, editorial or library science staff from manually tagging content. (2) By tagging data intelligently and according to best-practice standards, it significantly improves search engine optimization, primarily driven by solid metadata.
By making content dramatically more findable using its newly created semantic metadata, worker productivity is increased, as is external visibility of content on the Web. Increased visibility combined with increased relevancy (connecting and referring users to the RIGHT content) leads to improved Web site stickiness, and more time spent on a particular brand.
ProQuest, one of the world's largest information aggregators, uses Nstein to automatically tag over 75,000 articles from 2100 journals. A typical worker could handle 10 journals a day; the Nstein solution automates the work of 210 people, resulting in major cost savings.