Posts Tagged ‘Lexalytics’

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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Lexalytics’ Semantria Accommodates Text Analytics Abroad

lexsemInternational expansion has been a focus for cloud-based text and sentiment analytics vendor Semantria since its acquisition by text mining vendor Lexalytics over the summer. This week, that’s being addressed by adding enterprise text analytics servers in Europe, to address compliance with EU privacy laws around the location of personal data, as well as making its services available in Arabic, Russian, Japanese and Malay.

Lexalytics’ Semantria SaaS and Excel text-mining platform has a few clients in Europe so far, including among them several large social media monitoring and voice-of-the-customer clients that it’s signed up in the last quarter, according to Seth Redmore, VP Product & Marketing Lexalytics.  eDigitalResearch in the UK is one of them. English, French, German, Spanish, Portuguese and Italian are already among its supported languages, and Dutch should be next on board.

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Bottlenose Nerve Center Debuts, Bringing The Artificial Analyst To The Enterprise

rsz_botnosenewThe enterprise version of Bottlenose has formally launched. Now dubbed Nerve Center, the service to provide real-time trend intelligence for brands and businesses, which The Semantic Web Blog previewed here, includes a dashboard featuring live visualization of all trending topics, hashtags and people, top positive and negative influences and sentiment trends, trending images, videos, links and popular messages, the ability to view trending messages by types (complaints vs. endorsements, for example) and real-time KPIs. As with its original service, Nerve Center leverages the company’s Sonar technology to automatically detect new topics and trends that matter to the enterprise.

“Broadly speaking, every large enterprise has to be doing social listening and social analytics,” CEO Nova Spivack told The Semantic Web Blog in an earlier interview, “including in realtime, which is one thing we specialize in. I don’t think any other product out there shows change as it happens as we do.” It’s important, he said, to understand that Bottlenose focuses on the discovery of trends, not just finding what users explicitly search for or track. Part of the release, he added, “will be some pretty powerful alerting to tell you when there is something to look at.”

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Bottlenose Enterprise Wants To Be Your Artificial Analyst Team To Discover Trends And Insights

Bottlenose earlier this month raised $3.6 million in Series A funding to help with its launch of Bottlenose Enterprise, the upcoming tool aimed at helping large companies discover and visualize trends from among a host of data sources, measuring and comparing them for those with the most “trendfluence.” Users will get a realtime dynamic view of change as it happens and a host of analytics for automating insights, the company says.

The Enterprise edition will be a big departure from the current Bottlenose Lite version for individual professionals. That difference starts with the amount of data it can handle. “The free, Lite version looks only at public API data like Twitter’s. The enterprise version uses the firehose,” says CEO Nova Spivack. Another big difference is that the enterprise version adds a lot more views and analytics, in comparison to the personal-use edition, where its Sonar technology provides the chief service of real-time detection of talk around topics personalized to users’ interests so they can visualize and track those topics over time.

Spivack calls what Enterprise does “enterprise-scale trend detection in the cloud,” leveraging a massive Hadoop infrastructure and technologies including Cassandra, MongoDB, and the Storm distributed realtime computation system to process data for deep dives. The cloud handles the computation, and results are shared at the edge, where certain kinds of analytics and visualizations occur locally in the browser for a realtime expience with no latency. With sources such as social streams, stock information, even a company’s proprietary data, and more, the Enterprise version helps brands discover important trends like keywords to bid on or viral content to share, who are their influencers and detractors, what sentiment and demographic movements are taking shape, and to create correlations across data points, too.

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New Report May Help You Pick Your Text Analytics Vendor

A new report from Hurwitz & Associates seeks to put text analytics vendors in context. In an environment where unstructured text accounts for 80 percent of the data available to companies, the market analyst and research firm has prepared a Victory Index to help companies suss out who can best help them get value from this information.

By providing the ability to analyze unstructured text, extract relevant information, and transform it into structured information, “text analytics has become a key component of a highly competitive company’s analytics arsenal,” write report authors Fern Halper, partner and principal analyst; Marcia Kaufman, COO and principal analyst; and Daniel Kirsh, senior analyst. Often, the research firm notes, companies begin to experiment with text analytics to gain insight into the unstructured text that abounds in social media, and from that move on to other use cases. For instance, they’ll discover value in mining unstructured data and using it with structured data to improve predictive models.

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Taking Text And Sentiment Analytics To The Masses

Text and sentiment analytics for the masses. That could be a tagline for Semantria, which lets users put the technology to work in a pay-as-you-go cloud model. Not only that, but it lets customers deploy a plug-in to run analytics of unstructured content, extracting entities, themes, sentiment, categories, summaries, facets, and relationships, in one of the world’s most common user environments: Microsoft Excel.

More is on the way, too. This December should see the unveiling of a partnership with an as-yet-unnamed vendor to expand the applications with which its platform is compatible. That partner already offers data integrations with 300 applications; when Semantria becomes the 301st, users will be able to universally and bi-directionally talk to the hundreds of other applications without having to do any integration work on their own.

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Lexalytics Launches Salience 5.1

Lexalytics has announced a new version of the company’s Salience text analytics engine. According to the company, “This Salience 5.1 release includes several feature enhancements, including improved management of short content, resulting in improved sentiment accuracy for social media updates. The latest version offers both improved sentiment accuracy ‘out of the box’ (for both short and long content), as well as several new tools for configuring sentiment analysis to match business needs. Lexalytics has also changed the way it supports its foreign language offerings overall by adding the Concept Matrix™ to non-English languages. The Concept Matrix™ uses the entire human-generated encyclopedia, Wikipedia® (a registered trademark of the Wikimedia Foundation), and enables Salience to understand the complex relationships between words and meaning. Until now this functionality was only available in English.” Read more

Financial Services In The Spotlight At Sentiment Analysis Symposium

The financial services sector was in focus at this week’s Sentiment Analysis Symposium in New York City, which is organized and produced by Alta Plana Corp. and its founder, Seth Grimes.  Take, for example, the presentation by Rich Brown, head of Elektron Analytics at Thomson Reuters, who disclosed that the company is about to launch market response indicators in support of its Thomson Reuters News Analytics system for the financial community. That product this week also won The Technical Analyst’s 2012 award for best news analytics software.

With its software, originally discussed here, qualitative, unstructured information is turned into a quantitative data set allowing users – machines and humans – to quickly analyze thousands of news stories in less time than it takes to read a single headline, as Thomson Reuters describes it. It uses natural language processing technology to get to the end game, which is to forecast financial market response from news and social media sentiment. Some 82 fields of metadata come into play for automating the analysis of news content. That encompasses sentiment down through to the degree of positive, negative or neutral expressions and how individual companies mentioned in a piece fare in those respects – rather than just the tone of the piece at large. “The computational linguistics system measures the author’s tone as positive or negative on any given entity, which is important and the harder part of it,” Brown said. Other fields include, for example, relevance, genre, intensity of news flow, and more.

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Volume, Emotion, Sponsorship: What Brands Have An Edge on Social Media Strategies?

Market Strategies International recently released the first edition of what it says will be an annual Social Media Brand Index, a measure for brands both of consumer-generated social media about them and of their own sponsored content. The Index takes into account four components. Volume, or the amount of buzz about a brand online, is one of them — and its most highly weighted component, too. The others take their cue from what we might call more meaning-related measures, sentiment analytics and semantic markup among them.

For example, there’s net Sentiment, which Market Strategies says represents the ratio of positive to negative sentiments expressed about a brand based on automated natural language processing of the content of posts, comments and mentions. Another component, Positive Emotions, seems to flow from that measure, representing the number of content items that are identified as having the warm fuzzies about them, again based on automated coding of content.

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Lexalytics Amps Up the Semantic Understanding of Salience 5.0

Bill Ives recently discussed the advancements of Salience 5.0 with Lexalytics CEO Jeff Catlin. Ives writes, “Semantic technology differs from most computing as it learns on the job. This can provide great benefits but it can also be time consuming… [Lexalytics] came up with a clever idea to reduce the learning curve. They had their semantic engine digest Wikipedia to gain an understanding of human thought and build their Concept Matrices™. This allows it to do things that most computer technology would struggle with such as understanding that pizza is a food even though the word food was never associated with pizza in the text it was looking at.” Read more

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