Showing posts with label semantics. Show all posts
Showing posts with label semantics. Show all posts

08 November 2012

The BBC: from Auntie to Lady Semantica

The BBC is affectionately known in the UK as “Auntie”, probably for its gentle and slightly old-fashioned didactic style. But deep in its IT ecosystem, the huge broadcaster is a hot bed of innovation. Not for nothing is it ranked only second to Google as the “favorite place to work” for LinkedIn techie job seekers.

For anyone interested in how a major content publisher is embracing the challenge of language technologies, check out this long interview with BBC ‘semantic web’ people. After full-scale coverage of the World Football Cup last year and the London Olympics in 2012, the content team have been exploring all the implications of delivering tailored archival content for a cutting-edge online user experience. Or what LT-Innovate is calling “intelligent content”. 

Below is a summary of what they’re thinking about today:
“We are currently exploring various other uses of Semantic Web technologies within BBC R&D. In particular we’re looking at ways in which Linked Data can be used to help search and discovery of archive content. We have been working on automatically identifying the topics and the contributors for BBC programmes from their content, using a combination of Linked Data, signal processing, speech-to-text and Named Entity Recognition technologies, which we have been talking about in various places, such as the Linked Data on the Web workshop and at WWW’2012. The automatically generated links from programmes to entities described in the Linked Data cloud might be incorrect in places, so we are also exploring how users can validate or correct those links, and how this feedback can be taken into account within our automated interlinking workflow. We are planning to write in more details about our experiments in that space on the our blog in the next couple of weeks.”

Check out their blog to keep abreast of Auntie’s rapid reinvention as Lady Semantica. 

Author: Andrew Joscelyne

06 September 2012

Where Will Semantic Tech Be Better Commercialized - USA or Europe?

Where is semantic technology better poised to be better commercialized – the U.S. or Europe? At the last SemTech conference in San Francisco, 3RoundStones took first place in the Startup competition with Callimachus Enterprise. During a discussion of some of the product’s winning features, talk turned to some of the differences between how semantic technology has progressed in the States and overseas:

3RoundStones CTO David Wood
“I finally see the difference between Europe and the U.S.” “...The work done in R&D there (the UE) was very important and the large government projects were very impressive,” “In the U.S. we don’t spend a lot of money in top-down, federally funded R&D, and not in big central government data projects.” But what is here is a commercially-focused culture, and now large enterprises based here, seeing big vendors like IBM and Oracle talking up semantics, are buying into the idea of semantic tech in a bigger way. “...our projects, because they are economic in nature, are more sustainable.”

Antonia Bradford of the U.K.’s AB Computing
“There has been a lot of EU funding for semantic web projects and for semantic technology projects in general. There’s been funding at the government level and support in the university, but it does need to move out – it will never get anywhere if it stays in university labs,…or continues to receive government funding,” Bradford notes. 

Martin Bradford, primary developer at AB Computing
“The American model needs to take over and turn it into something that makes money for people.”

05 September 2012

Semantic Technology’s Role in Big Data Solutions?

Forbes has published an article that points out an opportunity for Semantic Technology companies. The article discusses the lack of understanding in companies around big data. The author, , concludes:

"Ready or not, the IT department can expect the business units to come back begging for help, just as they did in the 1990s. And even before business users start crawling back, I can imagine the red faces of all those IT executives that worked so hard in the last five years or so on establishing a “data governance” model for their companies and putting together master data management policies. The Garner analysts warned their listeners that big data “could break existing governance models.” This is similar to what Forrester analyst Boris Evelson wrote earlier this month: “You may find that all of your best DW, BI, MDM practices for SDLC, PMO and Governance aren’t directly applicable to or just don’t work for Big Data. This is where the real challenge of Big Data currently lies. I personally have not seen a good example of best practices around managing and governing Big Data. If you have one, I’d love to see it!”"

06 June 2012

Expert System announces the latest release of its Cogito semantic technology that takes Big Data management to the next level


Expert System, the semantic software company, member of LT-innovate, announces the latest release of its Cogito semantic technology, fortified with features to better support management of Big Data.

Given the quantity and diversity of information available, organizations need tools that provide a comprehensive view, not just single data points. Thanks to the ability to understand words in context, Cogito tackles the growing amount of unstructured information that often goes unanalyzed, but, when properly managed, can be the tipping point for competitive advantage. “The advantage of a semantic approach is its ability to provide access to unstructured information that, when integrated into your existing data, adds great depth and insight.” said Luca Scagliarini, VP, Strategy & Business Development, Expert System. 

The newest release of Cogito supports complex decision making by accessing all of the data available inside and outside the organization.

01 June 2012

La Stampa Chooses Semantic Technology to Improve Content Management


The leading Italian national newspaper La Stampa and Expert System today announce selection of the Cogito semantic software to improve the management of La Stampa’s editorial content. In the publishing world, rapid evolution of technology and fierce competition require adoption of new business models to stay ahead. Using Cogito, Expert System applies semantic technology to La Stampa’s online content, enriching it with metadata and enabling greater search and knowledge management, simplifying access and distribution of content and offering users more interactive tools for navigation and sharing. Semantic technology automatically processes articles published daily in both the print and online edition, associating each item with one or more relevant categories. In addition to an improved classification of news, La Stampa can now perform automatic tagging of items by identifying and extracting the information in content. This helps readers access new content related to the news they are reading, increasing both the time spent on the site, and the number of pages viewed for each access.

Irish Start-Up Sindice To Develop Value-based Semantic Web Technologies

Based at the Digital Enterprise Research Institute (DERI) in Galway, SindiceTech is developing new internet technologies based around advanced data management for enterprises. The company, a spin-out of NUI Galway, was set up by Giovanni Tummarello and Renaud Delbru with a team in DERI last year. 
Eight people are now working with SindiceTech and the company is looking to add three more. "Previous attempts of commercialising general semantic web technology have not focused in on the value and have failed," said Tummarello. "The alchemy here is combining large data processing capabilities with some of the principles of the semantic web, which have matured now and are an appealing value proposition for knowledge intensive technologies." 

SindiceTech helps large enterprises build their own strategic linked data clouds. The company was originally developed out of a research project around a search engine for the semantic web. 

29 May 2012

The LTi News Roundup - 27th May 2012 (part 2)

Weekly news round-up prepared by the Editorial Staff of LangTechNews for LT-Innovate, the Forum for Europe’s Language Technology Industry.

What's happening in the Language Technology industry, from LT-Innovate

Not searching, finding:

There was naturally a lot of coverage by the technorati of Google’s inclusion of semantic boxes in its search results. Plus claims that Chines search engine Baidu had been doing this already (and they say doing it better). Google’s Knowledge Graph reflects the on-going evolution from showing keyword hits to processing results into meaningful categories – people, places, etc. LT watchers will know that this semantic shift has been on the books for a long time. It even appears to mirror a certain view of how humans learn to process language: first collecting data (by listening to mum and dad), and then gradually finding patterns in these data. Somehow we then categorize patterns into meaningful units that give a virtual map of our communicative universe, aka concepts. 
And we test them by communicating with/about them with others. Google has indeed simultaneously published a concept dictionary (helped by work from the Ixa Group at the University of the Basque Country) that illustrates the relationships between data words and their semantic concepts. Also in the semantic space, PoolParty, the Semantic Information Management product from The Semantic Web Company, has announced a revamped version of its own semantic discovery application that demoes some of the conceptually-related information functionality that we shall soon come to take for granted when searching with any of our engines. 

Speaking of Market Size: 

Global Industry Analysts has published a report on the speech technology market in 2017, forecasting it will be worth about $31B ($3.3B of this for the IVR market). Ironically this is the same size as the global language services (outsourced translation and interpreting) market in 2011 as estimated by Common Sense Advisory. By contrast, analytics expert Seth Grimes estimated the size of the text analytics market to be “approaching $1B” last year, while Gartner says analytics is part of a $10B market for Business Intelligence software. Language services are growing by 7.4% a year, some estimates are that analytics is growing 25%/year. The speech tech market is also one of the fastest growing areas of ICT, and is expanding into new application areas almost by the week: from cars to healthcare to gaming to virtual assistants to security/identity to consumer interfaces and more. One example among many: BigHand, the UK recording/transcription supplier for lawyers and healthcare professionals, was acquired last week by investment company  Bridgepoint Development Capital, who intend to support the growth of its technology base (especially in SaaS) and footprint. This could perhaps spell less reliance on Nuance as its main supplier. BigHand had launched a major awareness-raising campaign earlier this year and seems convinced that this market is exploding. In what is clearly a big data world, speech tech suppliers like BigHand and especially contact centre managers will be able to exploit their vast collections of what analyst Dan Miller of Opus Research (specialists in the speech market) nicely calls “speechable” moments. Speech (and speech translation) technology developers need lots of data in various voices, dialects and styles covering multiple subjects to train their engines. One source could be recordings of interpreting, another could be contact centre conversations. Speech data from interpreting services (medical and legal events, or conference situations) have so far not featured on the LT radar. This is possibly due to IP and privacy constraints. Contact centres however, are now generating large recorded speech corpora. Both sources would offer a huge resource for companies building speech technology – and eventually translation services. 

22 May 2012

Challenges of sentiment analysis tools in Buzz monitoring sector


(...) If topics can be automatically classified in a relatively simple way, sentiment analysis (positive, negative or neutral) gets harder as it requires a global analysis of the monitored text. This may be particularly difficult in cases of coordination between different parts of a sentence, of an anaphora or of a coreference (the recovery of an argument later in this document). 

Another difficulty of natural language for automatic analysis of sentiments are intentional contexts, for which the expression of opinion is not a true feeling. Thus, the phrase" I thought the trams were more modern" may be identified as positive when the intention is, however, negative. If the analysis of conversations are established by "word packets", the sentences "I like this model not only because of ..." and "I did not like this model only because of ... "a real problem. They are composed of the same packet of words but represent an opposite feeling. Lucas Dini et al. "Showed the relationship between syntactic and semantic structures of a sentence and the expression of the opinion that vehicle". 

The algorithm must be able to differentiate a neutral comment (eg: this car announces a fuel consumption of 3.3 l/100km) from an opinion (eg: this car announces a fuel consumption of only 3.3 l/100km!). It should also detect spelling errors, simplified syntaxes, slang or smileys. Finally it may be that a comment has positive and negative elements. Are they equal in value or is it that the positives outweigh? The phrase "I think this car is the best in its segment ... but also the most expensive "is an example of such ambiguity. What did the author say ? It is normal that its price is more high because of its beauty or the contrary, the price is not worth the candle? Even a human would have difficulty assigning a tone here. (...)

Source : Master Thesis "Mobility sector in Belgium : social media monitoring to built an efficient marketing strategy" 2011, ULB.

Good News vs Bad News : the sentiment analysis tool that can change buzz monitoring practices

Across news sites, social media platforms, blogs and forums, customers are responding to what companies are doing every minute, but do we really know what they are saying ? As professionals we have all come across buzz monitoring or sentiment analysis tools to help us uncover the weak signals from the strong ones, but how usable are they ? 
You could be a trader looking for a quick and timely overview on the company you’re about to invest in, or a researcher wanting to understand the current landscape around a brand, the requirement for a tool that is usable and time efficient will be the same in most cases. 
That’s where Good News Vs. Bad News can help. "GoodNews Vs BadNews" is a free browser-based app that enables marketers, publishers and businesspeople alike to discover the positive and negative sentiments around their brand. The technology powering the application is comprised of a staggering 8 million lines of code and is used across the world by companies ranging from Microsoft to Motorola.

Source : LangTechNews

14 May 2012

The LTi News Roundup - 13th th May 2012 (part 1)


Weekly news round-up prepared by the Editorial Staff of LangTechNews for LT-Innovate, the Forum for Europe’s Language Technology Industry.

What's happening in the Language Technology industry, from LT-Innovate


Top of the Week : Exalead

Calling the French firm Exalead a ‘search company’ is beginning to sound silly. Now part of the Dassault Systèmes stable of product lifecycle management companies, it is stepping up its role as all-round innovation accelerator. This week it announced that two French start-ups will be developing new applications based on public data as part of Exalead’s role as incubator for the government Dataconnexions program. The idea is for these two young companies to explore marketable uses of government data, and one will be working on health data and the other on hyper-local information. They will both leverage Exalead’s Cloudview technology to develop their apps.

The Semantic Revolution

‘Semantics’ can be a weasel word in the ITC sector. In the discipline of linguistics it partners phonology and syntax as a level of language structure that addresses the meaning of words and sentences. In industry, on the other hand, semantics refers to the capacity to link data items together (ideally tagged with additional information).This can produce insights and applications that represent more than the sum of their parts. The German company Transinsight scored twice this week with its inventive data search-and-show technology driven by semantics. One project will be delivering an automated RSS news analyst to the Mayor of Dresden’s office which will enable rapid evaluation and decision-making. In a completely different field, it will provide interactive modelling software for the Norwegian company Statoil to help them visualise geodata. Other semantics companies in view include the UK firm Ontology Systems that ensures enterprise data alignment, and Concept Searching which released a new version of its flagship product.

03 May 2012

Cascaad joins LT-Innovate


Cascaad was founded in 2008 with the goal of making the online experience more personal and relevant. Their vision is to develop breakthrough discovery technology and products that can leverage social signals and individual interests to create better information consumption experiences. Cascaad is the company behind the consumer product : CircleMe. CircleMe is an inspiring social way to collect all your likes and discover new ones.
Cascaad focuses on developing technologies which allow to consume content online in a more personalized way. Cascaad’s technologies help the right content find users through a deep analysis on social graphs and social stream activity to create a current semantically-rich interest profile and social sphere of influence for a person, that can then be used to surface personally relevant content and ads.
Since establishment, Cascaad launched the following products: 

1) Cascaad Reader (web and iOS) 
2) Splice 


12 April 2012

LanguageTools joins LT-Innovate

LanguageTools was founded in Munich in 2008 to develop Linguistics, semantic search and web-mining solutions. It is a 100% privately owned and independent company with operations in Germany, UK and US. Since its founding Language Tools has experienced dynamic growth with about 8 full-time positions at this time. Language Tools is a technology-driven company combining linguistic expertise with novel data processing algorithms. Our vision is to provide the most accurate and in-depth analysis in milliseconds.
LanguageTools offers products and services with different levels of customization in the following areas:
LanguageTools website
LanguageTools profile on LT-Innovate
LT-Innovate members list
Join LT-Innovate