Posts Tagged ‘text analysis’

Dandelion’s New Bloom: A Family Of Semantic Text Analysis APIs

rsz_dandyDandelion, the service from SpazioDati whose goal is to delivering linked and enriched data for apps, has just recently introduced a new suite of products related to semantic text analysis.

Its dataTXT family of semantic text analysis APIs includes dataTXT-NEX, a named entity recognition API that links entities in the input sentence with Wikipedia and DBpedia and, in turn, with the Linked Open Data cloud and dataTXT-SIM, an experimental semantic similarity API that computes the semantic distance between two short sentences. TXT-CL (now in beta) is a categorization service that classifies short sentences into user-defined categories, says SpazioDati.CEO Michele Barbera.

“The advantage of the dataTXT family compared to existing text analysis’ tools is that dataTXT relies neither on machine learning nor NLP techniques,” says Barbera. “Rather it relies entirely on the topology of our underlying knowledge graph to analyze the text.” Dandelion’s knowledge graph merges together several Open Community Data sources (such as DBpedia) and private data collected and curated by SpazioDati. It’s still in private beta and not yet publicly accessible, though plans are to gradually open up portions of the graph in the future via the service’s upcoming Datagem APIs, “so that developers will be able to access the same underlying structured data by linking their own content with dataTXT APIs or by directly querying the graph with the Datagem APIs; both of them will return the same resource identifiers,” Barbera says. (See the Semantic Web Blog’s initial coverage of Dandelion here, including additional discussion of its knowledge graph.)

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Getting Europe Into The App Economy

In the United States, the app economy, as of late 2012, had created close to 530,000 jobs and served as a significant economic driver for a number of states. A study released by CTIA-The Wireless Association and the Application Developers Alliance, dubbed The Geography of the App Economy, reported more than 2.4 million apps available on more than 11 different operating systems and the stat that by 2016, mobile app revenue would be more than $46 billion.

Europe wants in. No wonder, when you see stats like the one from ABI Research this year that point to the combined app revenue from tablets and smartphones being projected to reach $92 billion by 2018, and to the app economy growing at 44.6 percent on average annually. But the continent needs some data to help it get its spot in the limelight, which is where Eurapp comes in.

The newly launched venture, Eurapp, was birthed by the European Commission, and is being run by the Digital Enterprise Research Institute at NUI Galway in conjunction with tech industry analyst firm GigaOM Research. It’s part of the Startup Europe initiative of the European Commission’s Digital Agenda, which aims to help tech entrepreneurs start, maintain and grow their businesses in Europe.  NUI Galway’s Dr John Breslin, SIOC creator and co-founder of iPad news and social reader app StreamGlider (see our story here) is leading the Eurapp project at DERI.

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Quant Finance Shops Can Add Sentiment About Macroeconomic and Geopolitical Events To Their Rules Toolbelts

Real-time macroeconomic and geopolitical events and sentiment about them now figure into RavenPack News Analytics 3.0, to help financial firms react more quickly to what’s happening in the world.

The solution is aimed at quant finance shops, such as hedge funds, banks, and some financial research houses, where the machines are doing the trading. It’s a part of the market that’s had some rough times of late because of some trading errors, but in general quant firms represent a growing piece of the financial space, says RavenPack Head of Sales and Business Development Hugh Taggart.

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Beyond Sentiment

[Editor's Note: This guest post is by Tom Reamy, Chief Knowledge Architect and founder of KAPS Group, a group of knowledge architecture, taxonomy, and eLearning consultants. Tom has 20 years of experience in information architecture, intranet management and consulting, and education and training software.  Tom will be presenting a tutorial, Text Analytics for Semantic Applications and moderating a panel, Emotional Semantics - Beyond Sentiment at the upcoming SemTechBiz Conference in San Francisco.]

photo of Tom ReamyWhile sentiment analysis continues to generate a lot of press, it is not clear how much real value organizations are deriving from it.  One reason for that is that the standard approach to sentiment has been mostly statistical and/or long lists of sentiment terms.  However, if you add in other, advanced text analytics capabilities such as auto-categorization using advanced operators, you can not only develop more sophisticated sentiment analysis, you can also develop a whole new class of applications that either enhance and/or go beyond simple sentiment analysis.

These advanced operators include such commands as DEST_6 (count two words as a positive indicator only if they are with 6 words of each other) or SENT (only count words in the same sentence).

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