Jennifer Zaino

Semantic Services May Benefit From Apigee Finetuning Its Edge API Platform

apigeeApigee is adding new capabilities to its Edge API digital business platform, including features that could be of use to applications that consume semantic services related to search or entity identification, for example.

Apigee Edge is designed to let companies and developers securely manage their APIs and to measure key metrics from API usage and traffic. Analytics always has been a core part of the platform, especially as it relates to providing real-time data to developers about how their APIs are being used, says Ed Anuff, VP products strategy at Apigee. With the introduction of API Traffic Analytics to the platform, it’s possible to measure metrics such as latency that can affect overall user experiences. “A lot of our customers asked for a better way to visualize that, to measure and view and set alerts to take steps to solve issues when latency is increasing.” says Anuff.

The challenge for developers working with semantic web technologies and processing services, he says, often comes down to making sure that you can deliver responsive results for the applications leveraging them.

“Oftentimes people find that the tradeoff of waiting a longer period of time for best results can be a challenge,” he says. “So the main thing that holds back the introduction of semantic enrichment to queries is making sure you deliver experiences where there is not variable latency.”

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Semantic Web Developer Challenge: We Have A Winner And Runners-Up Too

xsblogoThe results of the Semantic Web Developer Challenge, co-sponsored by XSB and SemanticWeb.com and launched at this summer’s Semantic Technology and Business Conference, are in: The $5,000 prizewinner was a team of two, Greg Varga and Siraj Bawa,  from Vanderbilt University. There were two runners-up: One was a team from Stony Brook University, comprised of Mrinal.Priyadarshi, Anurag Choudhary, and Paul Fodor, and the other was Roman Sova from consulting firm Good Monster.

The aim of the Challenge was to build sourcing and product life cycle management applications leveraging XSB’s PartLink Data Model, which the company developed as a project for the Department of Defense Rapid Innovation Fund. The model uses semantic web technology to create a coherent Linked Data model for all part information in the Department of Defense’s supply chain – which includes about 40 million component parts, their manufacturers and suppliers, materials, technical characteristics and more.

The large collection of engineering product information has potential beyond DoD use alone. “The current size of the Part Link triple store is well over a billion triples — maybe 1.3 billion,” says Alberto Cassola, vp sales and marketing at XSB. “For the industrial sector it may very well be one of the largest efforts of its kind.”

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Framed Data Gets Funding Round To Further Goal Of Helping Businesses Stop Customer Churn

framedataWant to keep your high-risk customers from heading out the door? Well, Framed Data wants to give you a hand.

The company, which today announced that it has raised $2 million from Google Ventures, Innovation Works, Jotter, and NYU Innovation Fund as well as a number of angels, applies machine learning to ending subscription churn. It’s focused especially on B2B SaaS companies, uncovering less than obvious behavioral traits of churned users and applying that knowledge for future use, says director of marketing Tim Wu.

“Churn is the biggest pain we can tackle,” he says, providing the company a way to distinguish itself in an increasingly commoditized data analytics space. And in the B2B SaaS market, “the lifetime value of customers is really clear – they know that if customers leave, they lose x dollars.”

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Yandex Takes Its Machine Learning Smarts Into New Role as Business Services Provider

yandex-logo (1)Yandex is going beyond web search and into the enterprise. This week it announced a new venture, the Yandex Data Factory, which will apply its machine-learning products and algorithms – which power more than 70 percent of its own products and applications – to business’ Big Data issues.

Using a client’s pre-existing data, the press release notes, Yandex creates an algorithmic model, which it then applies to the client’s new data to predict what will happen next in various scenarios. “This is exactly what is happening every second on Yandex’s services when we personalize search suggestions, recommend music, recognize speech or images, or target ads,” the release notes.

The model cases for Yandex Data Factory include: churn prediction by running segmentation and micro-segmentation algorithms on the data to find patterns in customer behavior that indicate they’re heading for the exit or that possible fraud activity is underway; personalizing cross-sell and up-sell recommendations based on user profiles built upon the searches they made, links or ads they clicked, videos they watched, and other activities; using its speech-to-text technology to analyze call center or other support call speech streams and detect anomalies in interactions to drive employee interaction quality and improve skills.

It also uses history-based prediction technology and its own computer vision and image recognition technologies to enables businesses to analyze large volumes of images and videos to spot anomalies, find recurring objects or events, and other things that will help them assess conditions and assure productivity.

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Smart Toys For Girls and Boys

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Courtesy: Flickr/ FutUndBeidl

Right before Thanksgiving The Semantic Web Blog gave readers a heads-up about how retailers use of semantic technology could help make the holiday shopping season brighter for consumers. This week, to help those still in need of finding something special for that someone special on his or her shopping list – i.e. friends, children and family with a taste for meaningful computing (or at least for the products that result from it) – we’ll take a look at some holiday gift buys that might fit the bill.

Ladies and gentlemen, start your shopping engines:

  • Joining his artificial-intelligence inspired robot friends like Robosapien X and Roboraptor is MiP, which toymaker Wowwee calls a balancing multifunctional and autonomous robot powered by iOS or Android smartphones. The device includes GestureSense technology that lets it respond to the motions of hands or other objects, so that you can play games like Follow the Leader, and to mobile apps that let you drive him around, set him up in a boxing match, or play games like stacking objects.

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Lexalytics Draws On Deep Learning To Enhance Salience 6 Text Analytics Engine

lexalThere’s a new version of Lexalytics’ Salience Text Analytics Engine: Some of its key new capabilities in Version 6 are enabled by underlying Syntax Matrix technology that the vendor has been working on for the last 12 to 18 months.

Syntax Matrix, explains vp of product and marketing Seth Redmore, takes on the job of doing efficient chunk parsing, so that customers who can be dealing with hundreds of millions of documents a day can maintain that scale without sacrificing accuracy or performance. “What [chunk parsing] means is that we can tear apart a sentence to understand quickly how all the phrases in the sentence relate to each other,” he says, much as Salience’s existing Concept Matrix technology leverages Wikipedia to help it tell what entities are related to each other and how closely.

Deep learning infuses the Syntax Matrix, which is trained on billions of words to support its rich approach to extracting phrases, each with some 200 different features associated with it. “With deep learning we extract so many different features and understand all the interrelationships between them,” he says, providing users with the chunks of the sentence that are most interesting to them, and what they mean so they can take action. “Sentiment Matrix lets us tear apart these sentences in a grammatically meaningful fashion and do it in such a way that you can build other stuff on top of it,” he says.

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Tamr On Mission To Curate And Connect Data

tamrlogoMake it as easy to add and connect new data sources into the enterprise analytics infrastructure as it is to add a new web site onto the modern web. That’s where next-gen data curation company Tamr, a startup born from an MIT research project to bring together lots of tabular data sources in a scalable and repeatable way.

Just like Google does all the work to find and connect web sites hosting the information that users want, “we want to do the same with tabular data sources inside the enterprise,” says Tamr co-founder and CEO Andy Palmer. “Tamr provides systems of reference. If you are looking for attributes to add to an analysis or want data to support something, you have this reference place to go in the enterprise with a catalogue of all the data that exists across the company.”

So often businesses want to use analytics to address hard questions, but can’t do so successfully unless they are integrating lots of disparate data sources and creating a referential catalog. With Tamr, Palmer says, they can ingest data sources very quickly into a semantic triple store, make them available in real time, and connect them using machine learning to map attributes and match records, in support of providing a unified view of a given entity that can then be consumed by various business intelligence and analytics tools. To be useable, he points out, data has to be “very, very thoroughly connected into everything else for there to be context and reference for how it can be consumed and whether it is reliable.”

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Taking On Turing, In Film And In Artificial Intelligence Workshop

turingnewThis past weekend the movie about British mathematician and computer scientist Alan Turing, The Imitation Game, had a successful debut. Turing, of course, created the Turing Test, which is a test of a machine’s ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human. Fittingly enough, tonight is the end date for entries to Google’s Imitation Game Code Cracking Challenge, a test designed to determine whether it’s being taken by a human or computer and which has as its focus the film’s principal character, Alan Turing. turing2

Judges this week will be evaluating entries this week, and should be contacting winners by week’s end, making their determinations based both on entrants submitting the correct codes and which entrants solved them the fastest. (The test went live in mid-November.)

Fun stuff, with prizes to include a screening of the movie in the winner’s hometown with 200 friends and signed-cast posters, but perhaps even more interesting is that come January, a group of scientists at the 2015 meeting of the Association for the Advancement of Artificial Intelligence, conduct a workshop to come up with a replacement of the original Turing Test. It’s aiming to create an annual or bi-annual Turing Championship, that might consist of up to five different challenging tasks, “with bragging rights given to the first programs to achieve human-level performance in each task,” according to a statement by workshop organizers Gary Marcus, Francesca Rossi and Manuela Veloso. Read more

Semantic Tech Lends A Hand To Thanksgiving Holiday Sales

Photo courtesy: https://www.flickr.com/photos/119886413@N05/

Photo courtesy: https://www.flickr.com/photos/119886413@N05/

Retailers are pushing holiday shopping deals earlier and earlier each year, but for many consumers the Thanksgiving weekend still signals the official start of the gift-buying season. With that in mind, we present some thoughts on how the use of semantic technology may impact your holiday shopping this year.

  • Pinterest has gained a reputation as the go-to social network for online retailers that want to drive traffic and sales. Shoppers get an advantage, too, as more e-tailers deploy Rich Pins, a feature made available for general use late last year, for their products, using either schema.org or Open Graph. Daily updated Product Rich Pins now include extra information such as real-time pricing, availability and where to buy metatags right on the Pin itself. And, anyone who’s pinned a product of interest will get a notification when the price has dropped. OverstockTarget, and Shopify shops are just some of the sites that take advantage of the feature. Given that 75 percent of its traffic comes from mobile devices, it’s nice that a recent update to Pinterest’s iPhone mobile app – and on the way for Andoid and iPads – also makes Pins information and images bigger on small screens.

 

  • Best Buy was one of the earliest retailers to look to semantic web technologies to help out shoppers (and its business), adding meaning to product data via RDFa and leveraging ontologies such as GoodRelations, FOAF and GEO. Today, the company’s web site properties use microdata and schema.org, continually adding to shopper engagement with added data elements, such as in-stock data and store location information for products in search results, as you can see in this presentation this summer by Jay Myers, Best Buy’s Emerging Digital Platforms Product Manager, given at Search Marketing Expo.

 

  • Retailers such as Urban Decay, Crate&Barrel, Golfsmith and Kate Somerville are using Edgecase’s Adaptive Experience platform, generating user-friendly taxonomies from the data they already have to drive a better customer navigation and discovery experience. The system relies on both machine learning and human curation to let online buyers shop on their terms, using the natural language they want to employ (see our story here for more details).

 

  • Walmart at its Walmart Labs has been steadily driving semantic technology further into its customer shopping experience. Last year, for example, Walmart Labs senior director Abhishek Gattani discussed at the Semantic Technology and Business conference capabilities it’s developed such as semantic algorithms for color detection so that it can rank apparel, for instance, by the color a shopper is looking for and show him items in colors close to read when red itself is not available, as well as categorizing queries to direct people to the department that’s really most interesting to them. This year, WalMart Labs added talent from Adchemy when it acquired the company to bring further expertise in semantic search and data analytics to its team, as well as Luvocracy, an online community that enables the social shopping experience—from discovery of products recommended by people a users trusts to commerce itself. Search and product discovery is at the heart of new features its rolling out to drive the in-store experience too, via mobile apps such as Search My Store to find exactly where items on their list are located at any retail site.

What’s your favorite semantically-enhanced shopping experience? Share it with our readers below to streamline their holiday shopping!

 

Cognitum Ontology Editor Amps Up Analytical Computations and Collaborative Knowledge Editing

fluenteditorlogoThe end of the month should see the release of an update to Cognitum’s Fluent Editor 2014 ontology editor, which will bring with it new capabilities to further drive its usage not only in academia but also in industrial segments such as energy, pharmaceuticals and more.

The company is including among its additions the ability to run analytical computations over ontologies with the open source language R and its Controlled Natural Language. What has been lacking when it comes to performing computations over Big Data sets, says CEO Paweł Zarzycki, is some shortcut to easily combine the semantic and numerical worlds. R is great for doing statistical analysis over huge sets of numerical data, he says, but more knowledge opens up when Cognitum’s language is leveraged for analysis in a qualitative way.

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