Jennifer Zaino

Alta Plana Takes The Pulse Of Text Analytics

wordcloudSeth Grimes, president and principal consultant of Alta Plana Corp. and founding chair of the Sentiment Analysis Symposium, has put together a thorough new report, Text Analytics 2014: User Perspectives on Solutions and Providers. Among the interesting findings of the report is that “growth in text analytics, as a vendor market category, has slackened, even while adoption of text analytics, as a technique, has continued to expand rapidly.”

Grimes explains that in a fragmented market, consisting of everything from text analytics services to solution-embedded technologies, the opportunities for users to practice text analytics is strong, but that increasingly text analytics is not the main focal point of the solutions being leveraged.

Reflecting the diversity of options, respondents listed among their providers a number of open-source offerings such as Apache OpenNLP and GATE, API services such as AlchemyAPI and Semantria, and enterprise software solution and business suite providers like SAP. The word cloud above was generated by Alta Plana at Wordle.net to show how users responded to the question of companies they know provide text/content analytics functionality. Nearly 50 percent of users are likely to recommend their most important provider.

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AlphaSense’s Advanced Linguistics Search Engine Could Buy Back Time For Financial Analysts To Do More In-Depth Research

alpha1When Raj Neervannan, CTO and co-founder of financial search engine company AlphaSense, thinks about search, he thinks about it “as a killer app that is only growing…..People want answers, not noise. They want to ask more intelligent questions and get to the next level of computer-aided intelligence.”

For AlphaSense’s customers – analysts at large investment firms and banks or any other industry, as well as one-person shops – that means search needs to get them out of ferreting through piles of research docs for the nuggets of information they really need. Neervannan knows the pain of trying to interpret a CEO’s commentary to understand what he or she was really saying when making the point that numbers were going down when referring to inventory turns. (Jack Kokko, former analyst at Morgan Stanley, is AlphaSense’s other co-founder.)

“You are essentially digging through sets of documents [using keyword search], finding locations of terms, pulling them in piece by piece and constructing a case as to what the company’s inventory turn was really like – what other companies’ similar information was, how that matches up. You have to do quantitative analysis and benchmarks, and it can take weeks,” he says.

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OpenText Takes Next Steps In Automatic Content Classification

otextOpenText yesterday made its secure file sharing and synchronization product, Tempo Box, available for free to customers using its OpenText Content Suite enterprise information management tool.

“A lot of our customers have major concerns about employees sharing documents with cloud tools like Dropbox,” says Lubor Ptacek, vp of strategic marketing. They want them to be available, synched and sharable across all their devices, but using such services can create security and compliance problems. By deploying Tempo Box on top of their existing infrastructure, at no charge to all internal employees and any external parties they may need to share content with, companies get a seamless and cost-effective way to share files in the cloud without compromising security, records management requirements and storage optimization, he says – “the things that enterprise customers care about, especially those operating in regulated environments.”

Among those capabilities is applying automatic content classification, which is usually required for records management reasons – for example, helping companies determine if a document is an employee record they must keep for five years or a tax record they have to hold for seven years. That under-the-hood classification engine is an outgrowth of OpenText’s acquisition a few years back of text mining, analytics and search company Nstein. Since the acquisition, says Ptacek, the company has been looking at ways to apply the technology to specific business problems and make it part of its applications.

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GraphLab Create Aims To Be The Complete Package For Data Scientists

glabData scientists can add another tool to their toolset today: GraphLab has launched GraphLab Create 1.0, which bundles up everything starting from tools for data cleaning and engineering through to state-of-the-art machine learning and predictive analytics capabilities.

Think of it, company execs say, as the single platform that data scientists or engineers can leverage to unleash their creativity in building new data products, enabling them to write code at scale on their own laptops. The driving concept behind the solution, they say, is to make large-scale machine learning and predictive analytics easy enough that companies won’t have to hire huge teams of data scientists and engineers and build the big hardware infrastructures that lie behind many of today’s Big Data-intensive products. And, the data scientists and engineers that do use it won’t need to be experts at machine-learning algorithms – just experienced enough to write Python code.

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Corporate Social Media: Sentiment Tracking Is Up, But Other Metrics Are Out of the Mix

insightThe State of Corporate Social Media is … well, strong might be too strong a word for it. The recently released State of Corporate Social Media Briefing 2014, from USM (Useful Social Media) finds – among other things – that social media team sizes are being reduced, fewer budgets are increasing, and fewer key performance indicators are being measured.

It’s not all negative. In fact, report author and USM founder Nick Johnson concludes that all together, its results could be interpreted as indicating that “social media within companies is beginning to mature, and the drive to leverage social to its full extent is undiminished.”

That said, the data equally could be interpreted to mean that “social media within companies is stagnating, and there’s an increasing lack of resources available to those within business to move forward to full leverage social’s potential.”

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Versium Leverages Microsoft Azure Machine Learning For New Predictive GivingScore Solution To Improve Fundraising

versiumpixVersium, which earlier this year launched its Predictive FraudScore solution (covered here) today releases its Predictive GivingScore solution, designed to help charitable institutions and political organizations better predict who is likely to donate, be a repeat donator, or make the more significant contribution. PredictiveGiving Score is the latest of the company’s predictive Score products, which also include churn, social influencer and shopper scoring – and it’s by no means the last.

It was built with Microsoft Azure Machine Learning, a managed cloud service for building predictive analytics solutions publicly unveiled just a short time ago. CEO Chris Matty says that platform is an aid to Versium in rapidly building its new score solutions. (Just shy of ten Versium scoring products are currently in use or in development.) Azure ML, Matty notes, contains dozens of machine learning algorithms and mathematical computation models it leverages to easily and effectively experiment, create and tune models to get the highest accuracy in predictive scoring solutions.

“Once we have a score built it just takes little tuning. But when we are building a new score we need to look at some different models and see what works better,” he says. “We want to move quickly by evaluating the different models, and we can visualize very easily the process of building the predictive model.”

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Daedalus Takes Meaning-As-A-Service To Excel, GATE And CMS Systems

meaningasaserviceDaedalus (which The Semantic Web Blog originally covered here) has just made its Textalytics meaning-as-a-service APIs available for Excel and GATE (General Architecture for Text Engineering), a JAVA suite of tools used for natural language processing tasks, including information extraction in many languages. Connecting its semantic analysis tools with these systems is one step in a larger plan to extend its integration capabilities with more API plug-ins.

“For us, integration options are a way to lower barriers to adoption and to foster the development of an ecosystem around Textalytics,” says Antonio Matarranz, who leads marketing and sales for Daedalus. The three main ecosystem scenarios, he says, include personal productivity tools, of which the Excel add-in is an example, and NLP environments, of which GATE is an example. “But UIMA (Unstructured Information Management Applications) is also a target,” he says. The list also is slated to include content management systems and search engines, among them open source systems like WordPress, Drupal, and Elasticsearch.

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Spiderbook’s SpiderGraph: Linking Datasets To Help You Sell Better

spiderpix1Startup Spiderbook, which is building a linked dataset of companies and their partners, customers, suppliers, and people involved in those deals, has recently closed its seed round for $1 million. The next-generation sales intelligence company was co-founded by CEO Alan Fletcher, who was a vp of product engineering, IT and operations at Oracle, and Aman Naimat, who has been working in the realm of CRM software since he was 19 years old and also has a background in natural language processing. Along with other core members of the team, the company puts natural language processing and machine learning technology to work to help sales people better connect the dots that explain business relationships, extracting information from unstructured text to sell more effectively.

State-of-the-art CRM, says Naimat, by itself doesn’t help salespeople sell. Since the days of Salesforce, which he worked on at IBM and Oracle, it has remained the same thing, he says, “just evolving with better technology. But basically it is an internal-facing administration tool to give management visibility, not to help a salesperson sell or create business relationships.”

Built from billions of data elements extracted from everything from SEC filings to press releases to blogs to Facebook posts, Spiderbook’s SpiderGraph is taking on that challenge, starting with the goal of helping salespeople understand who is the right contact to talk to, how he or she can meet that person (through shared contacts, for instance), and who competitors are, including those providing technology or other products already in use at the company. “We have created a graph of customers, competition, and suppliers for every company that is all interconnected,” he says.

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Setting Government Data Free

taAs July 4 approaches, the subject of open government data can’t help but be on many U.S. citizens’ minds. That includes the citizens who are responsible for opening up that data to their fellow Americans. They might want to take a look at NuCivic Data Enterprise, the recently unveiled cloud-based, open source, open data platform for government from NuCivic, in partnership with Acquia and Carahsoft. It’s providing agencies an OpenSaaS approach to meeting open data mandates to publish and share datasets online, based on the Drupal open source content management system.

NuCivic’s open source DKAN Drupal distribution provides the core data management components for the NuCivic Data platform; it was recognized last week as a grand prize winner for Amazon Web Services’ Global City on a Cloud Innovation Challenge in the Partner in Innovation category. Projects in this category had to demonstrate that the application solves a particular challenge faced by local government entities. As part of the award, the NuCivic team gets $25,000 in AWS services to further support its open data efforts.

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IBM Watson Group CTO Discusses Cognitive Computing, Content Curation For Healthcare Market

robhighThe role that cognitive computing can play in healthcare was explored last week in this story published at The Semantic Web Blog’s sister site Dataversity.net. That article looked at how Modernizing Medicine is leveraging IBM Watson for its new schEMA tablet app that helps doctors use the wealth of published medical research from highly reputable sources, such as the Journal of the American Medical Association (JAMA) and New England Journal of Medicine, to answer their questions.

Today, we’re complementing that article to further explore such aspects of the health care and cognitive computing connection based on an email conversation with IBM Watson Group CTO Robert High. “IBM Watson is transforming the patient experience and healthcare delivery system by helping physicians make sense of the enormous amount of data generated by an increasingly connected healthcare environment,” High writes.

“Content curation is a critical part of the solution delivery process. Without reputable and reliable sources of medical literature, therapy choices offered by Watson may not have the supporting evidence needed to inform clinicians in the use of those treatments. We work with the top clinicians at our partners to collect their feedback on supporting evidence and cull inappropriate information from their sources.” IBM, along with its solutions partners, works with a variety of content providers based on the relevance of their materials to treatment options, he adds.

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