Posts Tagged ‘NLP’

Semantic Technology Job: R&D Engineer

IPsoft logoIPsoft needs a R&D Engineer. The job description states, “Amelia is the next generation human-computer dialog system that acts as your personal student, instructor, assistant, or friend.  Amelia is based on the latest state-of-the-art technologies in natural language processing, information retrieval, machine learning, and more.What distinguishes Amelia from previous generation human-computer dialog systems is its learning ability.  Amelia is capable of understanding syntax and semantics of natural language and automatically builds its own neural ontology from them.  If you want to teach Amelia about a certain object, you simply describe the object in natural language, then Amelia builds a neural ontology for the object automatically.  Once the neural ontology is built, Amelia can explain or answer questions about the object by traversing through the ontology.  Objects do not have to be specified upfront; you can talk about random stuffs and expect Amelia to build neural ontologies for objects that are newly introduced during your conversation with Amelia.  When you ask questions about things that Amelia does not have neural ontologies for, Amelia tries to find the most appropriate answer from the World Wide Web.  These include questions about weathers, current events, historical/geopolitical facts, etc.”

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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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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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Blab Builds The Conversation Graph

blab2We have the Knowledge Graph, the Enterprise Graph, the Researcher Graph, the Supply Chain Graph – and now, the Conversation Graph, too

That’s how Blab characterizes the work it’s doing to add structure to the chaotic world of online conversation, normalizing and patterning the world’s discussions across 50,000 social network, news outlet, blog, video and other channels, regardless of language – to the tune of some hundred million posts per day and 1 million predictions per minute. Near realtime predictions, says CEO Randy Browning, of what a target audience will be interested in a 72-hour forward-looking window based on what they’re talking about now, so that customers can tailor their buying strategies for AdWords or search terms as well as create or deploy content that’s relevant to those interests.

“We predict what will be important to people so they can buy search terms or AdWords at a great price before the market or Google sees it,” he says. That’s the main reason customers turn to Blab today, with optimizing their own content taking second place. Crisis management is the third deployment rationale. “If a brand has multiple issues, we can tell them which will be significant or which will be a blip and then fade away, so they can get a predictive understanding of where to focus their resources to mitigate issues coming down the pike.

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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

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

A Deeper Look at Common Sense Reasoning

Siri LogoCatherine Havasi, CEO of Luminoso recently wrote for Tech Crunch, “Everyone knows that ‘water is wet,’ and ‘people want to be happy,’ and we assume everyone we meet shares this knowledge. It forms the basis of how we interact and allows us to communicate quickly, efficiently, and with deep meaning. As advanced as technology is today, its main shortcoming as it becomes a large part of daily life in society is that it does not share these assumptions. We find ourselves talking more and more to our devices — to our mobile phones and even our televisions. But when we talk to Siri, we often find that the rules that underlie her can’t comprehend exactly what we want if we stray far from simple commands. For this vision to be fulfilled, we’ll need computers to understand us as we talk to each other in a natural environment. For that, we’ll need to continue to develop the field of common-sense reasoning — without it, we’re never going to be able to have an intelligent conversation with Siri, Google Glass or our Xbox.” Read more

Startup Adatao Raises $13M to Bring Search to Big Data

adataoDeborah Gage of The Wall Street Journal reports, “Making big data stores as easy to search as Internet data has been a holy grail for the software industry, and it’s become a more pressing problem since the growth of the big data software Hadoop, which holds enormous amounts of data. Adatao Inc., a startup based in Sunnyvale, Calif., has raised nearly $13 million in Series A funding led by Andreessen Horowitz to take on the challenge. Founded in 2012 by veterans of Google Inc., Yahoo Inc. and the Army Research Lab, the company combines machine learning, natural language processing and in-memory (i.e. fast) computing to create a system in which users can write queries in ordinary English or one of several computer languages-—Smart Query, SQL, Scala, Java, Python or R–and get results in less time than it takes to speak their questions.” Read more

How Natural Language Processing and Big Data are Making Sense of Consumer Behavior

ATTENSITY LOGODana Gardner of CRM Buyer recently wrote, “The power of Big Data technology is being successfully applied to understanding such complex unknowns as consumer sentiment and even intent. That understanding then vastly improves how retailers and myriad service providers manage their users’ experiences — increasingly in real time. Fortunately, today’s consumers are quite willing to share their intents and sentiments via social media, if you can gather and process the information. Hence the rapidly developing field of social customer relationship management, or Social CRM.” Read more

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