Company News

Is Paris Hilton a celebrity socialite or a hotel in France? The answer depends upon the context, perhaps from a Web page, magazine article, or other source. A normal search engine can’t tell the difference – but semantic technology can.

Jeff Catlin, Lexalytics’ CEO, discusses text mining in hospitality.

“Semantics, syntax, and context.” You need all three to turn text into possible business decisions, according to Seth Redmore, CMO at Lexalytics, Inc.

Reports on Caitlyn (formerly Bruce) Jenner’s recent debut on the cover of Vanity Fair have cited an assortment of reactions from the Twittersphere.

Lexalytics, a provider of cloud and on-prem text and sentiment analytics solutions, updated its Salience sentiment analytics platform.

In this special guest feature, Jeff Catlin of Lexalytics lays out the case for text analytics and its importance to the rising interest in big data.

Lexalytics®, a leader in cloud and on-prem text and sentiment analytics solutions, announces the update of its Salience® sentiment analytics platform with quicker, more accurate processing, easier configuration of query topics in accented languages such as Portuguese and Spanish, and the ability to contextualize sentiment statements using Boolean search logic.

Lexalytics, a provider of text and sentiment analytics, today launched a wizard and graphical user interface (GUI) for its Semantria software-as-a-service (SaaS) platform and Excel plugin. The new wizard, called SWIZ, is part of the Semantria Online Configurator, SWEB 1.3.

Customer-strategy maven Paul Greenberg made a thought-provoking remark to me back in 2013. Paul was puzzled — Why haven’t there been any billion-dollar text analytics startups?

Tesla Motors experienced its second highest one-minute trading volume of all time earlier this month after computers misinterpreted the company’s April Fools’ Day joke as a serious press release.

You’ll often hear organisations claim to be “at the beating heart” of a country’s digital industry. In the case of a new tool launched by IAB South Africa, that’s a little more literal than you might expect.

Most tools in the booming field of analytics rely on quantitative data. Analytics tends to work best with large numbers of numerical data points; smaller data sets and those where the data isn’t easily quantified can present problems.

The Internet Advertising Bureau of South Africa’s mission is to promote digital growth and in doing so, has to tap in to what South African internet users are talking about. Once brands know that, they can react and start talking to consumers

Catherine Havasi wants to help businesses understand what people are saying on Twitter, Facebook, and other online feeds and forums—right now. Havasi is the co-founder and CEO of artificial intelligence startup Luminoso

Lexalytics is going beyond predicting consumers’ feelings, or sentiment analysis, to anticipating their actions with what they call “intention analysis.” Information Week takes a look at the feature

Luminoso, a sentiment analysis startup with DNA from MIT’s Media Lab, says its new product can take consumer feedback from Twitter, Facebook, Google+ and potentially other feeds, and boil it into one stream to provide a near real-time look at how people feel (or at least talk) about a given topic.

Big Data has been a hot topic in the business world in recent years. Even if consumers aren’t quite sure how it all works, they know its purpose: Companies are collecting and using digital data — such as Web search histories, past purchases and geolocation — to make personalized recommendations and market to customers in the most targeted, effective way possible.

L’efficacité avec laquelle les terroristes recrutent sur l’internet a créé une commotion mondiale. Plus que jamais, les services secrets sont pressés de les traquer sur ce terrain. Des percées technologiques renversantes, qu’on pensait réservées aux oeuvres de science-fiction, pourraient bientôt les y aider. Elles n’en inquiètent pas moins les défenseurs de la vie privée.

2014 saw 39 companies in social media analysis change hands, a big jump from the 18 in 2013. Continuing an ongoing trend, most of the year’s deals involved strategic technology acquisitions or specialist firms joining bigger companies

Брюки и пиджак, смокинг с галстуком‑­бабочкой или джинсы ­­и поло? Олег Рогинский, 26‑летний владелец стартапа Semantria, не может подобрать подходящий костюм. Он собирается на ужин со своим бывшим боссом Джеффом Катлином, генеральным директором

In my previous post, I described the future of enterprise search. In this post, I will describe few new search applications that could be interesting.

While I am admittedly a newcomer to the field of sentiment analysis, I was interested in seeing how the breaches at Sony and Staples affected the public perception of the companies.

В недавно опубликованном исследовании управляющий партнер AVentures Capital Евгений Сысоев вместе с коллегами проанализировал 250 сделок, в которые за последние три года было вовлечено свыше 1000 украинских стартапов.

As has been our tradition these last few years, The Semantic Web Blog steps back for experts in it and in related spaces to give us their opinion of the highlights of 2014. Here is Part 1:

One of the great things about following big data is that every so often, when you want to touch on its “creepy factor,” you get to link to the New York Times story of how Target figured out a teen-age girl was pregnant before her father did (the link is to the lengthy original; this Forbes’ columnist summarizes it nicely).

Lexalytics intention analysis tool determines what you’re going to do before you do it, the company says. This goes beyond sentiment analysis.

There’s a new version of Lexalytics’ Salience 6 Text Analytics Engine, with some of its key new capabilities enabled by underlying Syntax Matrix technology that the vendor has been working on for the last 12 to 18 months.

Voice of the Customer specialist eDigitalResearch has partnered with Lexalytics, foremost provider of text and sentiment analysis software, to develop an industry leading real-time text analytics tool.

This last year has seen a proliferation of predictive apps which Forrester has described as “the next big thing in app development.” These apps, backed by predictive APIs, have brought machine learning to the masses.

Docurated, a document management platform provider, published a remarkable compilation of essays. The collection of industry experts’ views appeared in May 2014 as “Enterprise Search: 14 Industry Experts Predict the Future of Search.”

There was a time, not too long ago, when the general population would have bet their life savings that flying cars and human-like robots would exist by the year 2014.

A review of AlchemyAPI, OpenCalais, and Semantria

Lexalytics, an 11-year-old company that sells text-analytics software for companies’ on-premises data centers, has found a cloud option for itself, by buying a startup called Semantria.

Sentiment analysis is an important tool for businesses looking to get a better understanding of how their customers feel about their products. Instead of surveys that offer abstract ratings, it lets companies look at the emotions underlying how users talk about their goods or services.

Social media is a difficult thing to manage for many companies. Most high-ranking business people think Twitter is a goldmine, and the best place to find information about their Next Big Thing™.

Seth Redmore, Lexalytics’ VP of Marketing, discusses the future of enterprise search.

Choosing the right keywords for search is the most important component of getting the results you’re looking for. Everyone knows this, but it’s easier said than done. Even with the most well thought out keywords, search results don’t always deliver

When you read the title of this article, you must wonder what I’m talking about when I say, “That’s sick!”

It makes sense if I just witnessed a car accident so heinous that it made me feel sick to my stomach. However, it also makes sense if I just saw Sidney Crosby score the game-winning goal for the gold medal game at the 2014 Socchi Olympics. A difficulty with linguistics is that the same word can have multiple meanings.

Since its inception, social media has evolved to become one of the greatest tools in the modern marketer’s arsenal. But, while companies use this emerging medium to disseminate brand messaging and conduct customer service, individual consumers use social media as their personal mouthpiece, sounding off about whatever’s on their mind.

Your customers want to communicate with you. Your partners, employees, potential clients, competitors, press and social media influencers want to communicate with you too.

Humans communicate in a wide variety of ways – body language, eye movement, intonation of speech, hand gestures, use of color and clothing. There is no system on earth that can yet capture all of the wide bandwidth of communication that we all use, as we go through our days.

If there’s one piece of advice I can offer you, both for better text mining and better writing, it is this: please, please, please with a cherry on top, be clear with your pronouns.

Organizers of the Sentiment Analysis Symposium scheduled March 5-6 in New York at the New York Academy of Sciences announced today that technology leaders IBM, Dell, Lexalytics, and Gnip, and best-in-class solution providers Textalytics, SentiMetrix, TheySay, Celi, SementicForce and Coverseon, have extended their support as sponsors.

Interest in text analytics is growing as companies begin to understand its value in providing insights into unstructured text. With maturing of the technology, it’s now possible to analyze very large amounts of data. In this interview, Seth Redmore with Lexalytics provides insights into dealing with text as data, getting started in text analytics, and how companies are realizing a competitive advantage with text analytics.

I recently had the opportunity to speak at length with Oleg Rogynskyy, CEO and Founder of Semantria, one of the leading text analytics firm. At its core, text analytics refers to deriving high quality information from text. This has become increasingly challenging in recent years as the amount of unstructured data has exploded.

In his 1997 management classic The Innovator’s Dilemma, Harvard professor Clayton Christensen coined the term disruptive innovation. The central premise was that a change in technology can completely transform the basic economics of an business. Business of Software – Clay Christensen When Clayton Christensen first envisioned disruptive innovation, he probably never imagined that the cloud would disrupt everything.

This is the third in a series of columns assessing the readiness of text and social analytics to play a productive role in enterprise solutions. In this column, I assess approaches to acquire analytics applications when dealing with a common institutional barrier: the chief information officer (CIO).

Are you looking for the most efficient and effective Top 30 software for Text Analysis, Text Mining, Text Analytics ? Text Analytics uses statistical pattern learning to find patterns and trends from text data. SAS Text Analytics, Smartlogic, Angoss, Clarabridge, AeroText, IBM SPSS, NetOwl, Attensity, Autonomy, Language Computer, Lexalytics, Basis Technology, Lexalytics, Endeca Technologies, Expert System, Medallia, IBM LanguageWare, Sysomos and WordStat are some of the key vendors in this area.

The future. The year 1997, or 2003, or 2011. Judgment Day. When Skynet wreaks havoc on the world, the machines rise up, and take us all out. Or at least, that’s how it happened in the Terminator movies and TV series.

The field of deep learning is picking up steam to the point that it’s now inspiring a growing list of startups in areas such as natural language processing and image recognition.

Oleg Rogynskyy’s goal is to democratize text analytics, and turn it into the coolest thing on the block. He is the founder and CEO of Semantria, a text and sentiment analysis startup that’s disrupting the market.

We were trying to bring as much information as we could from our backend into Eloqua, in order to better understand our users, their current and future needs, as well as their problems.

The Center for Data Innovation spoke with Oleg Rogynskyy, the founder and CEO and founder of Semantria, a sentiment and text analytics startup based out of Montreal.

One of the data visualisations that you can use with Oracle Endeca Information Discovery is the “tag cloud”. You’ve probably seen tag clouds used in newspaper articles and other publications to show the most commonly found words or phrases in a document

This is part of a series of posts to share with readers a useful collection of some of the most important, effective and practical data visualisation-related resources. This post presents a collection of useful tools, resources and references for gathering, cleaning and preparing your data for analysis and design.

I would disagree with the notion that there is no magic bullet for sentiment analysis. Lexalytics Salience Engine gives 65-70% prevision out of the box which has been proven by majority of our customers.

In the last years we have witnessed how the explosion of social media, rather than just providing an easy way of generating and publishing new personal content, collaterally offers a real-time source of information that shouldn’t be wise to ignore by any company that aims for customer satisfaction (and which isn’t?). That´s why today we want to talk about Twitter and Oracle Endeca Information Discovery.

This is a list of summarizer APIs, libraries, and software. We’d like to keep this list fresh so feel free to suggest additions – chris@mashape.com . Enjoy!

Use Cases – Lexalytics Salience (10:00-23:00)

Angoss Software Corporation, a Canada-based provider of analytics software and solutions, has entered into an agreement to partner with Lexalytics, Inc., a US-based company engaged in building text analysis engine, to advance Angoss’ big data analytics capabilities and improves the accuracy of predictive analytics modeling by increasing the types and volume of data that can be analyzed to include unstructured, text-based data.

Lexalytics, a provider of text and sentiment analysis software, said that its CEO, Jeff Catlin, will be presenting on how companies can maximize business results using social media insights at the upcoming Sentiment Analysis Symposium held in New York on Tuesday, May 8.

Link-sharing and shortening platform Bitly has launched a new social media monitoring service for businesses which spots “potentially damaging” threats to brands before they “spiral out of control”.

Many news organizations are pressing a new frontier of technology in 2012 — training computers to analyze thousands of written messages and interpret how their authors feel.

A new cloud platform has been launched for Twitter users, allowing them to mine more than two years of historical tweets to extract insights and identify trends relating to businesses, brands, financial markets, news and public opinion.

While in San Francisco, we spoke with Seth Redmore of Lexalytics. During this fun video, we chatted about sustainable technology, social business, storage solutions and more.

Social data processing specialist launches searchable archive of tweets going back to January 2010.

Social media architects have been so busy creating the future that they’ve often given short shrift to the past.

The perishable nature of the status post may have started to change on Facebook, with its new Timeline profiles, but history is still hard to come by on Twitter, where search results typically don’t reach back more than days or weeks. Individual users may value Twitter precisely for how well it lives in the moment, but researchers seeking to analyze changing attitudes and trends often need to look backward in order to tell what has changed.

No humans required, or that’s the premise.

Lexalytics which is best known for its text analysis engine highlights their text summarization tool.

Symposium will feature speakers and panelists from American Express, Fidelity Investments, Kraft Foods, the Red Cross, Thomson Reuters, and Yahoo, start-ups, and academia

Net Promoter, a mainstay of marketing measurement, is being adapted to the social media age with a Klout-like rating system based on the ratio of pro and con opinions on Twitter and Facebook

On its own, Twitter builds an image for companies; very few are aware of this fact. When a big surprise happens, it is too late: a corporation suddenly sees a facet of its business – most often a looming or developing crisis – flare up on Twitter

Sentiment and text mining analytics company Lexalytics has created the first easy to use semantic classifier by compiling over 1.1 million words and phrases from Wikipedia. Sentiment analysis, or opinion mining, refers to the application of natural language processing, computational linguistics, and text analytics to identify and extract subjective information in source materials.

As the child of TweetMeme, one of the most successful search and aggregation frontends to Twitter, DataSift aims to power sophisticated search, filtering, and analytics for applications.

One of my two or three readers sent me a link to “Acquisition: The Elephant in the Meeting Room.” I don’t have strong feelings one way or the other about Mongoose, the write up, or the enterprise search sector. I have identified some of the buzzwords used to dance around the little-discussed problem of lousy enterprise search systems.

DataSift, a real-time data-filtering platform, is moving stateside to help businesses monitor just how their brand is doing when it comes to social media.

Essentially, DataSift’s platform searches through user conversations on social media sites (just Twitter for the time being) to formulate business-related insights based on hundreds of millions of social media posts per day. The platform is also able to filter social media data by demographic information, online influence and sentiment.

Sentiments come into play thanks to a partnership with Lexalytics…

In the past few years, savvy companies have been using text analytics software to analyse positive and negative phrases appearing in social media and other electronic posts to figure out what customers think about their products, service and policies.

I feel expansive today (November 9, 2011), generous even. My left eye seems to be working at 70 percent capacity. No babies are screaming in the airport waiting area. In fact, I am sitting in a not too sticky seat, enjoying the announcements about keeping pets in their cage and reporting suspicious packages to law enforcement by dialing 250.

As Jason has reported before here, sentiment analysis is a tricky thing. Even humans disagree on sentiment 15 percent of the time, so how can a computer create something more accurate? As technology evolves, sentiment analysis gets better, or so we’d like to think.

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.

Semantic technology differs from most computing as it learns on the job. This can provide great benefits but it can also be time consuming. I recently talked with Jeff Catlin, CEO of Lexalytics, about what they’re doing with their recent upgrade of their product, Salience 5.0.

A good example of the buy out that slays the competitor is Thomson Reuters’ purchase in October 2011 of some of the intellectual property, people, and software from Infonics Lexalytics.

Link shortening and social web analytics provider Bit.ly announced today the first Enterprise product built on top of its new search platform, a reputation tracking alert system

Lexalytics competes in the realm of text analysis. Its Salience engine helps companies track what people are saying about their products on the internet. Seth Redmore, VP of Product Management at Lexalytics, talks sentiment analysis with David Cox in, “Train Your Computer, Monitor Your Brand Online Using Sentiment Analysis.”

A variety of API-fronted services offer strong semantic-analysis capabilities: Resolution of entities, facts, relationships, and sentiment in text originating in online, social, and enterprise sources. Our first meetup this year will feature service presentations from representatives of innovative players including Lexalytics, Pingar, and Saplo and continue with a moderated discussion of the start of the technology and the market, trends, and directions.

I am tired, in a weird time zone, and in a place that looks like the moon. I took time out from some exciting meetings to read “When Patents Attack Android”. I would have made “android” plural, that’s why I am in the middle of nowhere and Google is sitting on top of the mobile world.

Gee it’s quiet. That’s because most everyone is on vacation, preparing for one, or thinking about one.

August is get-away month, so the hospitality industry should start gearing up for what happens when all those travelers get back home….and start to record their impressions of the properties at which they stayed across the social media landscape

Attention all marketers, market researchers, analysts, and the like! If you’re in the mood to learn and schmooze in San Francisco’s autumnal sunshine, this year’s Sentiment Analysis Symposium — taking place in early November — features in-depth discussions on sentiment analysis of enterprise, online, and social content.

With the advent of social media customers today have multiple channels to express how they feel about a product or service. But how can companies efficiently capture all such comments to derive overall trends and meanings?

Viva Las Vegas! And if I’m “viva-ing” Las Vegas, I’d stay at the luxurious Bellagio. So why, when comparing the Bellagio to the like of Bally’s on TripAdvisor, did Bally’s have a higher score? It seems mind-boggling to me and made Lexalytics, who generated TripAdvisor’s online review scores, scratch there collective heads as well. In the Forbes article “Text Analytics Show Why Bellagio Underperforms Bally’s” Lexalytics went beyond the score and analyzed the actual text of the reviews to get some answers.

Algorithmic trading on the news (see Deutsche Bank story below), measuring responses to political speeches and figuring out why the Bellagio underperforms Bally’s, are all part of the work Lexalytics performs through analyzing text in news stories and social media.

A few weeks ago I received a pitch saying that Lexalytics, a B2B provider of sentiment and text analytics technology, powering brand and reputation management tools such as Radian6 and Scout Labs, had recently upgraded their Salience product by digesting all of Wikipedia to come up with their patent-pending technology, Concept Matrices.

En el reino de tuitilandia cada día se envían algo más de 50 millones de tuits (frente a 200.000 millones de correos electrónicos). A 140 caracteres por tuit, equivale aproximadamente al contenido de un disco de siete gigabytes. Un marasmo de mensajes cortos, la mayoría irrelevantes, inconexos en su conjunto, dedicados a la comunicación de un instante.

To gain a trading edge, Wall Street traders are now using clever computer programs to monitor and decode the words, opinions, rants and even keyboard-generated smiley faces posted on social-media sites like Twitter.com.

Whether you embrace or scorn Wikipedia as a reference, there is at least one good use for it, according to Lexalytics. “Lexalytics Analyzes Wikipedia to Understand How Humans Think” describes the rewards of their idea for an alternative function for the user-edited online dictionary.

Lexalytics, whose text and sentiment analytics engine underpins media monitoring solutions from vendors such as Radian6 (the recent acquisition target of Salesforce.com) and Scout Labs, has a new version of its Salience software that digested every bite of knowledge inside Wikipedia and built an understanding of the relationships between words and meaning to deliver its new Concept Matrix and dependent capabilities such as Facets and Collections.

Concepts extracted from the community created encyclopedia can be used to improve analysis of documents and sentiment in social media.

Lexalytics, Inc. has announced a major upgrade to its Salience product, bringing semantic features to the forefront.

Sys-Con Media brought this news to our attention in their article, “Lexalytics Announces Salience 5.0, an Evolution in Semantic Understanding.” Lexalytics has created Concept Matrix by digesting the entire human generated encyclopedia, Wikipedia®. This was done to help the software understand the complex relationships between words and meaning – the core of semantic technology.

You can learn a lot from Wikipedia, despite all its faults—and Jeff Catlin’s company has done just that.

Boston-based Lexalytics said today that its latest text-analysis software incorporates insights from combing through Wikipedia’s entire user-generated online encyclopedia for relationships between words, phrases, and their meanings.

Jeff is appearing on the “Visionaries” panel at the Sentiment Analysis Symposium on April 12. I’ve corresponded with Jeff for several years and always find his thoughts and guidance insightful and provocative. We’ll finally meet at the panel, and I’m looking forward to it.

North American organizations can now keep track of online news, blogs and social media in multiple languages using MediaVantage, a web-based application for media intelligence and public relations

Semantic technologies can “make search engines better or more precise in finding relevant content,” says Moulton. So if your company operated a retail Web site, that would mean that semantically-enabled searches would do a better job of leading shoppers to your site and then helping them find products they want to buy.

The number-crunchers on Wall Street are starting to crunch something else: the news.

Math-loving traders are using powerful computers to speed-read news reports, editorials, company Web sites, blog posts and even Twitter messages — and then letting the machines decide what it all means for the markets.

Growth in visibility, acceptance, and adoption of automated sentiment-analysis solutions has been fueled by vendor innovations and by positive customer experiences, reports Elizabeth Glagowski in 1to1 magazine. Liz interviewed me for her article, and with her permission, I will share the full text of our exchange with readers…

A bit of controversy regarding sentiment analysis is playing out. A techno-skeptic blogger clique asserts that automated sentiment analysis is so inaccurate as to render automated methods worthless. Others differ with them: we like automation. Newly joining us are some of the skeptics’ own kind, critics such as “Measurement Queen” K.D. Paine…

Sentiment-analysis technologies aren’t perfect. But what critics are missing is the value of automation, the inaccuracy of human assessment, and the many applications that require only “good-enough” accuracy.

Companies such as JetBlue have used it to mine e-mails and other customer feedback for insight.