Apixio raises $13.5M to bring NLP to health care

Apixio has raised a $13.5 million series C round of venture capital from Bain Capital Ventures and several angel investors. The company’s technology extracts data from numerous types of medical records, including patient charts and doctors’ notes, in order to help hospitals and insurance companies get a better sense of patients’ health for risk-assessment purposes. Apixio has raised more than $22 million since launching in 2009. It first launched publicly in 2011, then focusing on its semantic-analysis engine for identifying latent connections between diagnoses and symptoms.

If machines can perform sentiment analysis accurately, how will that change business?

Recent research at Stanford (see Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank, Richard Socher, et al) seems to have advanced sentiment analysis of text to a new level of about 85.7% accuracy for full sentences, if the authors are to be believed. Imagine that the state of the art might soon be approaching 100% accuracy: what would be the impact on business?

Marketing has moved dramatically in recent years away from surveys and focus groups, toward social listening: monitoring what people in social networks are saying about product, brands, and activities related to them. Marketing staff are vacuuming up comments about products, campaigns, and promotions, and trying to respond in real-time, as well as logging all the data for later analysis.

If machinery can do all or part of this, then an increasing part of the jobs of marketing, customer support, and other functions (like HR) might be accomplished by machinery geared to sentiment analysis, and AI-based approaches to taking next steps based on individual and aggregated sentiment.

It may also be that a large part of what middle managers do involves sentiment analysis. Consider tools like 15five or Tiny Pulse (see TINYpulse is a small and simple anonymous feedback tool), which are intended to be a quick technique to get a handle on staff sentiment. But if semantic analysis and AI can compbine to do all or part of that job, managers might be able to spend their time doing other things, or managing a larger number of people.

This is perhaps a codicil to the piece I wrote earlier today, How many of today’s jobs could be computerized? A whole lot. This may be part of the wave of technological advancement that the researchers I reported on in that piece were talking about.

It pays to know you: Interest graph master Gravity gets $10.6M

Interest graph specialist Gravity has raised $10.6 million to expand its business of personalizing the web for consumers. Thanks to a semantic engine that associates the content site visitors read with related topics, Gravity says it can show readers just what they want to see.

How Atigeo uses semantics to make search interactive

Sure, you can trust a site is delivering you the best search results, but sometimes it might be nice to dig down, see a little of what the system sees and find that needle in the haystack. A new semantic search interface might let that happen.

DataPop scores $7M for custom-built ads

DataPop, a startup using big data to deliver custom online ads, has raised a $7 million Series B round. The company’s technology uses big data techniques such as natural-language processing and semantic association to automatically generate online ads based on what a web user has searched for.

Can big data fix a broken system for software patents?

Legal scholars are always searching for ways to improve the patent system, sometimes via sweeping changes, but big data — especially techniques such as machine learning and natural-language processing — could help provide a technological fix to a big part of the problem.

ADmantX raises $2.8M for semantic ad technology

Semantic ad tech company ADmantX has raised $2.8 million in funding from Atlante Ventures Mezzogiorno, the venture arm of Italian bank Intesa Sanpaolo. The funds come just a few months after ADmantX came out of beta to provide ad targeting based on semantic analysis.