The Top NLP Mistake Made by Data Scientists
When the conclusions seem “off,” is it bad data science or faulty NLP? By Dan Maxwell Download Whitepaper Executive Summary In the age of big data, high-quality results from natural language processing (NLP) data ...
Learn more
Serco
Imagine what it takes to collect, process, and adjudicate 11 million applications every year, with the vast majority happening within a surge period of 135 days. That is what Serco ...
Learn moreRosette 1.17.0 Release: Hebrew Name Translation, French Semantic Similarity, Robust Address Matching
Recent Rosette® Cloud and Enterprise releases (1.17.0, 1.16.1) bring expanded language coverage to name translation and semantic similarity, and ease of use to the address matching capability within Rosette Name ...
Learn moreBuilding a More Useful Hebrew Transliteration Scheme
When the Rosette® Name Translator team set out to build a Hebrew-to-Latin character translator, one of the first considerations was: Which Hebrew transliteration standard should we use? As the joke ...
Learn moreFaster Annotation with Rosette Adaptation Studio
What are the top three barriers to better machine learning models? Annotating data, annotating data, and annotating data. Okay, so it’s not that simple, but producing quality training data to produce ...
Learn moreWelcome to Being Human, X Æ A-12
Elon Musk’s Son X Æ A-12, Presents the Ultimate Name Matching Challenge The naming of a child is an intrinsically human activity. Your parents get the first crack at it, but ...
Learn moreA Day in the Life of… Building a New Entity Extraction Model
What does it take to build a real production-ready model for entity extraction in one language? Here’s a peek through the eyes of our linguistic data engineer. Swedish model building by ...
Learn moreHootsuite
Hootsuite is the most widely used social media management platform, trusted by more than 18 million people and employees at 80% of the Fortune 1000. Clients of Hootsuite are empowered ...
Learn moreMake Your Choice: It’s More Than a Score for Evaluating NLP
Part 3 of Evaluating Natural Language Processing for Named Entity Recognition in Six Steps Just as standardized test scores alone cannot prove that an applicant will be successful in a college ...
Learn moreEvaluating NLP: Annotating Evaluation Data and Scoring Results
Part 2 of Evaluating Natural Language Processing for Named Entity Recognition in Six Steps In our previous blog post, we discussed the importance of defining your requirements for your NLP evaluation. ...
Learn moreEvaluating NLP: Assembling a Test Dataset
Part 1 of Evaluating Natural Language Processing for Named Entity Recognition in Six Steps How do you know if a given natural language package will do what you need? How can ...
Learn more
U.S. Customs & Border Protection
U.S. Customs and Border Protection (CBP) provides security and facilitation operations at 328 ports of entry throughout the country. CBP takes a comprehensive approach to border management and control, combining ...
Learn moreDeep Learning Brings Fuzzy English-to-Japanese Name Matching Into Focus
Matching thousands of Latin-based names to their Japanese equivalent is a very specific and troublesome problem. It is one of many “edge cases” (i.e., a specific name matching problem) ...
Learn more