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Here’s a simple task: given the sentence “Any good restaurants near Ballard or Fremont?” figure out what the person is referring to. Where are Ballard and Fremont? What are Ballard or Fremont? This (relatively) simple task illustrates the challenges of AI and machine learning. How do we train a language model to understand the intent of the query and resolve any entities as accurately as a person would but much faster?
We’re excited to be introducing the latest version of the Repustate Text Analytics API, version 4. The new version launches June 1, 2018. This new version brings new API calls for Semantic Search, our state of the art semantic search engine, as well as new API calls for entity recognition. While v4 is mostly about the new API calls being added, some changes are being made to existing API calls.
Repustate is announcing today the release of its new product: semantic analysis. Combined with sentiment analysis, Repustate provides any organization, from startup to Fortune 50 enterprise, all the necessary tools they need to conduct in-depth text analytics. For the impatient, head on over to the semantic analysis docs page to get started.
(This is a guest post by Sarah Harmon. Sarah is currently a PhD student at UC Santa Cruz studying artificial intelligence and natural language processing. Her website is NeuroGirl.com) Using Repustate’s API to to get the most out of TripAdvisor customer reviews I’m a big traveler, so I often check online ratings, such as those on TripAdvisor, to decide which local hotel or restaurant is worth my time.
A core function that any text analytics package needs is to do language detection. By language detection, we refer to the following problem: “Given an arbitrary piece of text of arbitrary length, determine in which language the text was written.” Might sound simple for a human, assuming you know a thing or two about languages, but we’re talking about computers here.
Never content with where we are, we’ve been working hard at improving all aspects of our software offerings. Our original service, sentiment analysis, has long been due for an upgrade and today I’m pleased to announce a new version of our engine. It’s faster, much more accurate, has a much smaller code footprint and easier to reason about for us developers.