Posts Tagged ‘natural language processing’

IBM Watson Chief Mike Rhodin on What Watson Has Taught IBM

WatsonBarb Darrow of GigaOM recently wrote, “IBM’s Watson natural language query/cognitive computing prodigy was a huge PR coup for Big Blue. Three years ago, Watson defeated Jeopardy champ Ken Jennings on national TV and beat other challengers like a drum on a subsequent victory tour. (Ask Gigaom’s own Stacey Higginbotham about that sometime.) IBM rode that wave for years to show that despite its woes, it can still do really hard stuff. IBM wants Watson to be a $10 billion business by 2023. But, unfortunately for IBM, there is ‘not a lot of commercial application to playing Jeopardy,’ Mike Rhodin, IBM SVP for Watson, acknowledged at Emtech 2014 at MIT on Tuesday.IBM invested untold millions in Watson, so it’s now time for Watson to, in the tortured words of another Emtech presenter, become ‘a market-based solution’.” Read more

Unearthing Data on Non-Public Companies with Artificial Intelligence

datafoxGreg MacSweeney of Wall Street and Tech recently wrote, “It’s relatively easy to find information on public companies. Bloomberg, Thomson Reuters, and Dun & Bradstreet, for example, all have in-depth information that is accessible to anyone with a subscription. But where do investment bankers, venture capitalists, and other investors find reliable information about private companies? If you talk to investment bankers, or other investors who are looking for information on non-public companies, it quickly becomes apparent there is no easy answer. Investment bankers rely mostly on Google searches and a combination of information gathered from Hoovers, S&P Capital IQ, Dun & Bradstreet, and others. But it is a laborious manual process to do due diligence on private companies.” Read more

Clarabridge Goes Straight To The Customers’ Mouth To Analyze Call Center Interactions

cbridge logoCustomer experience management vendor Clarabridge wants to bring the first-person narrative from call center interactions to life for marketing analysts, customer care managers, call center leaders and other customer-focused enterprise execs. With its just released Clarabridge Speech, it now brings via the cloud a solution that integrates Voci Technologies’ speech recognition smarts with its own capabilities for using NLP to analyze and categorize text, sentiment and emotion in surveys, social media, chat sessions, emails and call center agents’ own notes.

Agent notes certainly are helpful when it comes to assessing whether customers are having negative experiences and whether their loyalty is at stake, among other concerns. But, points out Clarabridge CEO Sid Banerjee, “an agent almost never types word for word what the customer says,” nor will they necessarily characterize callers’ tones as angry, confused, and so on. With the ability now to take the recorded conversation and turn it into a transcript, the specific emotion and sentiment words are there along with the entire content of the call to be run through Clarabridge’s text and sentiment algorithms.

“You get a better sense of the true voice of the customer and the experience of that interaction – not just the agent perspective but the customer perspective,” Banerjee says.

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Contify Relies on NLP, AI, and Machine Learning for new Competitive Intelligence Platform

contifySugandh Dhawan of iamwire.com reports, “New Delhi based SaaS startup, Contify, has launched an enterprise grade competitive intelligence (CI) platform to cater to the large organisations dealing with the job of identifying, sourcing, curating, and disseminating critical business information, across several functions. Founded in 2009 as a content syndication business, Contify is a product company focused in the areas of machine learning, artificial intelligence, and natural language processing.  It offers an intelligence platform to enable businesses to monitor their competitors, customers and industries along with critical market variables that impact ones business.” Read more

Natural Language Processing Market Booms

Reports-n-Reports logoA recent press release indicates that, “The Natural Language Processing (NLP) market is estimated to grow from $ 3,787.3 million in 2013 to $9,858.4 million in 2018. This represents a Compounded Annual Growth Rate (CAGR) of 21.1% from 2013 to 2018. In the current scenario, web and e-commerce, healthcare, IT and Telecommunication vertical continues to grow and are the largest contributor for Natural Language Processing (NLP) software market. In terms of regional growth, North America is expected to be the biggest market in terms of revenue contribution. European and APAC region is expected to experience increased market traction, due to increasing adoption across various verticals and investment support in research projects from the regional government ”.

The release also states, “The major forces driving natural language processing market (NLP) are the growing demand for enhanced customer experience, increase in adoption of smartphone, leveraging big data and growth in machine to machine (M2M) technologies. Furthermore, in industries such as healthcare, BFSI, social websites and e-commerce channels have witnessed exponential rise in real time customer data and transaction information. NLP technology can leverage this unstructured data for analyzing customer needs, expectations and enhancing customer experience by optimizing cost effective lingual response system in organizational processes. By using NLP software solutions, organization can have better insights on customer’s perception, optimize business processes and reduce operational cost.”

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Semantic Technology Job: Natural Language Processing Expert

morfologica logoMorfologica, Inc. is looking for a Natural Language Processing expert. The job description states: “Morfologica Inc. is a small business that provides consulting and engineering services in the fields of Natural Language Processing (NLP) and Computational Linguistics to academic, business and government organizations. We are a growing company with lots of opportunities and great benefits for qualified candidates with a passion for this field. We are looking to support a customer in the Fort Meade area by adding experienced NLP Experts, Computer Scientists, Computational Linguists, Theoretical or General Linguists, and Knowledge Engineers to our team. Qualified candidates with a strong background in Artificial Intelligence, Cognitive Science or Library Science are also encouraged to apply. Interested candidates will be working at a customer site supporting ongoing research efforts for NSA.  The work being done will include development and testing of parsers, part-of-speech taggers, Wordnet applications, and processing of multi-lingual data. The ideal candidate will have a strong understanding of one or more natural language processing techniques, knowledge-base or rule-based developent, and programming experience in NLP-related technologies. The candidate will also have on-going experience providing consulting and support in fields related NLP. Individuals with continued experience with multiple NLP tools and techniques are preferred.”
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IBM Taps Global Network of Innovation Centers to Fuel Linux on Power Systems for Big Data and Cloud Computing

ibmCHICAGO, Aug. 22, 2014 /PRNewswire/ — At the LinuxCon North America conference last week, IBM (NYSE: IBM) announced it is tapping into its global network of over 50 IBM Innovation Centers and IBM Client Centers to help IBM Business Partners, IT professionals, academics, and entrepreneurs develop and deliver new Big Data and cloud computing software applications for clients using Linux on IBM Power Systems servers. Read more

GetSet Hopes to Reduce Drop-Out Rates with Natural Language Processing

getsetNatasha Lomas of Tech Crunch reports, “GetSet, a new stealthy US edtech startup that’s aiming to reduce the high college drop-out rate is uncloaking today and revealing its first rollout at Arizona State University, with its 10,000+ freshmen. First up, in case you’re feeling a spot of deja vu, last week TechCrunch covered a UK startup called Wambiz that’s taking aim at the same problem. Yes, yes, you wait ages for college drop-out reduction startups and then two come along at once. So it goes. That said, they’re not identical. Wambiz is building an engagement platform cum social network as a better way to reach/engage with students, rather than sending comms via more traditional channels like email and SMS.” Read more

Yahoo Acquires Local Search App Zofari

zofariMenchie Mendoza of TechTimes recently wrote, “Affectionately described as a ‘Pandora for places,’ Zofari’s acquisition seemed to have attracted less attention when the deal was announced last week. Zofari uses natural language processing, machine learning, and third party data to collect information that matches up the user with places which the user may find interesting. The financial terms of the acquisition have not been revealed. On Zofari’s official site, the company confirmed that four of its employees are joining Yahoo. They are identified as Oliver Su, Shahzad Aziz, Jason Kobilka and Nate Weinstein. ‘After meeting some of the amazing folks on the Yahoo Search team and hearing about their vision, the decision for our team to join Yahoo was an easy one,’ said in the announcement. ‘We can’t talk about what we’re working on yet, but needless to say we are very, very excited’.” Read more

How SwiftKey is Using NLP and AI to Revolutionize the Keyboard

swiftSteve Ranger of Tech Republic reports, “Qwerty [the standard keyboard layout] was a compromise from the start. And as such you’d expect it to be swept away as the technology changed. And yet this odd layout became the standard, used since on billions of devices from typewriters to tablets and PCs. Even as the cold steel of the typewriter was replaced by the cool glass of a touchscreen smartphone, Qwerty has continued to dominate. That is, until now. A number of companies are rethinking the keyboard for the digital age, led by a small UK startup called SwiftKey, so that a mere 150 years after it was first created, the keyboard could finally be made to behave just how the user wants it to.” Read more

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