Posts

Sep 19, 2017 NLP and Consumer Insights
Social media provides a medium for consumers to rant, rave, and recommend products, brands, and services. This digital voice of the customer provides brands, and the agencies serving them, insights into the when, where, how, and why products are used, who is buying them, who is using them, and information about those individuals including their associated beliefs, needs, wants, and preferences. These insights facilitate understanding of consumer behavior, which can allow brands to better build, design, and market their products and services to meet consumers’ needs and desires. Given that the majority of the consumer conversation is textual in nature (e.g. product reviews, tweets, Facebook posts, etc.), Natural Language Processing along with Machine Learning and, in more general, Artificial Intelligence are now critical components in gaining a 360 degree view of consumers.
Jun 13, 2016 Hermes 0.3
Hermes 0.3 has been released. This version brings a unified interface to annotations, attributes, and relations, lots of bug fixes, and most importantly an almost usable user guide.
Feb 11, 2016 Hermes 0.2
Hermes 0.2 is almost ready for release. Key additions will be the integration of Apollo for machine learning, a part-of-speech tagger, shallow parser, WordNet interface and annotator, and numerous improvements and bug fixes. Modules have been refactored to move malt parser into core. Informal benchmarking on an i7 shows ~40K words per second for tokenization, sentence segmentation, part-of-speech tagging, and dependency parsing. More improvements to come!
Jan 21, 2016 Introducing Apollo
Apollo is a “yet another” machine learning and math library for Java. Apollo is meant to be the ML backbone for the Hermes NLP framework. The ultimate goal for Apollo is to allow local and distributed training to be done seamlessly much like corpora are handled in Hermes and streams are handled in Mango.
Jan 17, 2016 An Overview of Hermes
Hermes is a Natural Language Processing framework for Java inspired by the Tipster Architecture and TextBlob. Hermes focuses on simplifying the development and use of NLP technologies by providing a framework to quickly access and construct linguistic annotations on documents using multiple cores or multiple machines (using Apache Spark). At the core of Hermes is the HString which acts like a Java string on steroids.