Category Archives: Application Areas of Text Analytics

Posts about Application Areas of NLP / Natural Language Processing / Text Analytics

Semantic Publishing: a Case Study for the Media Industry

Semantic Publishing at Unidad Editorial: a Client Case Study in the Media Industry 

Last year, the Spanish media group Unidad Editorial deployed a new CMS developed in-house for its integrated newsroom. Unidad Editorial is a subsidiary of the Italian RCS MediaGroup, and publishes some of the newspapers and magazines with highest circulation in Spain, besides owning nation-wide radio stations and a license of DTTV incorporating four TV channels.

Newsroom El Mundo

Newsroom El Mundo

When a journalist adds a piece of news to the system, its content has to be tagged, which constitutes one of the first steps in a workflow that will end with the delivery of this item in different formats, through different channels (print, web, tablet and mobile apps) and for different mastheads. After evaluation of different provider’s solutions in the previous months, the company then decided that semantic tagging would be done through Daedalus’ text analytics technology. Semantic publishing included, in this case, the identification (with disambiguation) of named entities (people, places, organizations, etc.), time and money expressions, concepts, classification according to the IPTC scheme (an international standard for the media industry, with around 1400 classes organized in three levels), sentiment analysis, etc.

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Our new Semantic Publishing API is now available in MeaningCloud

This API allows you to produce and publish more valuable contents, more quickly and at lower costs

UPDATE: this API has been discontinued. Use instead our Solution for Semantic Publishing, featuring APIs like Topics Extraction, Text Classification and Automatic Summarization.

At MeaningCloud we keep developing our roadmap and offering new vertical APIs, optimized for different industries and applications. We are pleased to announce that our Semantic Publishing solutions include a new API, designed especially for media, publishers and content providers in general.

It is a logical step for us, since at MeaningCloud we have been collaborating for years with the most significant enterprises in these industries (PRISA, Unidad Editorial, Vocento, RTVE, lainformacion.com, etc.) and this is one of the markets where we are detecting more demand and where our solutions are gaining more traction.

The Semantic Publishing API incorporates the know-how we have been developing when working with these large companies and packages it in the form of semantic resources, process pipelines and specific configurations for the most common applications and scenarios of this industry: archive management, content generation, customization of information products, etc.

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Textalytics sponsors the Sentiment Analysis Symposium

Next March 5-6, New York will host a new edition of the Sentiment Analysis Symposium. This is the seventh event of a series organized by industry expert Seth Grimes since year 2010 in San Francisco and NYC.

This is a unique conference in several aspects. First, it is designed specifically to serve the community of professionals interested in Human Analytics and its business application. Second, its audience is integrated by a mix of experts, strategists, practitioners, researchers, and solution providers, which makes a perfect breeding ground for discussion and exchange of points of view. Third, it is designed by just one person (not by a committee), a guarantee of consistency. Being an expert in the consultancy business, Seth Grimes achieves an excellent balance of presentations covering from technology to business application. I attended the New York 2012 edition, where I gave an enlightening talk, and I can tell that the experience was really enriching.

Sentiment Analysis Symposium 2014

Do not be misled by the title: do not interpret “Sentiment Analysis” in a narrow sense. The conference is about discovering business value in opinions, emotions, and attitudes in social media, news, and enterprise feedback. Moreover, the scope is not limited to text sources: speech and image are terms of the equation too.

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Semantic Analysis and Big Data to understand Social TV

We recently participated in the Big Data Spain conference with a talk entitled “Real time semantic search engine for social TV streams”. This talk describes our ongoing experiments on social media analytics and combines our most recent developments on using semantic analysis on social networks and dealing with real-time streams of data.

Social TV, which exploded with the use of social networks while watching TV programs is a growing and exciting phenomenon. Twitter reported that more than a third of their firehose in the primetime is discussing TV (at least in the UK) while Facebook claimed 5 times more comments behind his private wall. Recently Facebook also started to offer hashtags and the Keywords Insight API for selected partners as a mean to offer aggregated statistics on Social TV conversations inside the wall.

As more users have turned into social networks to comment with friends and other viewers, broadcasters have looked into ways to be part of the conversation. They use official hashtags, let actors and anchors to tweet live and even start to offer companion apps with social share functionalities.

While the concept of socializing around TV is not new, the possibility to measure and distill the information around these interactions opens up brand new possibilities for users, broadcasters and brands alike.  Interest of users already fueled Social TV as it fulfills their need to start conversations with friends, other viewers and the aired program. Chatter around TV programs may help to recommend other programs or to serve contextually relevant information about actors, characters or whatever appears in TV.  Moreover, better ways to access and organize public conversations will drive new users into a TV program and engage current ones.

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MeaningCloud – Meaning as a Service: our new SaaS offering

A few weeks ago we were talking on here about how Daedalus (now called MeaningCloud) has explored various API-based business models for marketing its semantic technologies. Our perception was that basic language features are hard to use for many developers —not experts in these technologies— and require them to build solutions through a process of trial and error, in a do-it-yourself fashion, which is slow and inefficient.

Our vision was to offer the market APIs with a more plug-and-play philosophy, which provide a functionality closer to the business, a faster learning curve and, as a result, an increased productivity. That vision has crystallized in our product Textalytics and today we can say that it is now available.

Textalytics is the easiest way to embed semantics into your applications

Textalytics (now called “MeaningCloud”) is a SaaS offering that provides a high-level multilingual semantic processing functionality to those developers / integrators who want to develop semantic solutions in an effective, quick and cheap way. Compared with other semantic offerings in service mode, MeaningCloud offers several APIs, each with a specific functionality which is close to an application domain, and SDKs, plug-ins, etc. that make its learning and use much easier, reducing the effort required to obtain results and time-to-market.

Textalytics - Meaning as a Service

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