February 1, 2013
In his AI3 blog, semantic technology pro Mike Bergman presents a new series of articles on “Enterprise-Scale Semantic Systems.” Bergman and his business partner recently gained some eye-opening experience while deploying enterprise-wide semantic systems, and wanted to share their new insights with the world.
The article starts with some history on semantic technology, beginning with the World Wide Web Consortium’s (W3C) adoption of the Resource Description Framework as a standard in 1999. Bergman describes early developments and high hopes for the technology, as well as certain disappointments that followed. Once one turns away from the unrealized grand visions, however, the actual possibilities are quite promising, if not so dramatic. Though information management within the enterprise remains problematic, Bergman sees reason for hope:
“Daily we see success of semantic technologies in multiple locations, and the market is coming to understand the uses and potential benefits. The benefits of graph-based knowledge structures in search and recommendation systems are becoming accepted. We see how basic search is being enhanced with entity recognition and characterization, as well as richer links between entities. The ability of the RDF data model and ontologies to act as integration frameworks is no longer an assertion, but a fact. Despite the despair of some semantic advocates, the market place is increasingly understanding the concepts and potential of semantic technologies.”
While insisting that there is good money to be made in this field, Bergman lists some factors which continue to make implementing enterprise-wide semantics a challenge. For example, many businesses still doubt that it is a wise investment, though he says the demonstration of improved search functionality often seals the deal. Not surprisingly, budget constraints are another prominent hurdle.
If this first article is any indication, expect the series to include a lot of detailed explanations and tips for approaching enterprise-scale semantic systems. A worthwhile read for anyone in that field.
Cynthia Murrell, February 01, 2013
January 28, 2013
The decline in the pricing of RAM and the popularity of cloud computing in conjunction with the need for faster queries has produced a multitude of options for enterprise organizations to increase productivity and efficiency. O’Reilly Radar discusses the demand for technology and tools that facilitate interactive query performance. The article “Need Speed for Big Data? Think In-Memory Data Management” explains how these tools lead to real-time communication and reports.
The article informs us about interactive query performance:
Faster query response times translate to more engaged and productive analysts, and real-time reports. Over the past two years several in-memory solutions emerged to deliver 5X-100X faster response times. A recent paper from Microsoft Research noted that even in this era of big data and Hadoop, many MapReduce jobs fit in the memory of a single server. To scale to extremely large datasets several new systems use a combination of distributed computing (in-memory grids), compression, and (columnar) storage technologies.
We have seen an increase in the amount of technologies available to address engagement and productivity issues in the workplace, but there are none that we have seen to match the user experience and infrastructure technology of PolySpot. This solution enables information access while maintaining data integrity and adding semantic enrichment. What more could an analyst or a decision-maker want?
Megan Feil, January 28, 2013
Sponsored by ArnoldIT.com, developer of Beyond Search.
January 4, 2013
Sandpiper Software released news that they will be rolling out a visual ontology modeler. Their new release, “Sandpiper Software Inc. Announces Visual Ontology Modeler for Semantic Modeling,” provides more information. One interesting aspect is that the VOM measures up to standards from the Object Management Group (OMG).
The OMG standards are leading the industry in defining interoperable enterprise applications. The VOM enables users to access and unlock capabilities and functions in current information stores.
Elisa Kendall, CEO of Sandpiper Software made the following statement:
“Ontology modeling will give businesses the ability to capture, share and retrieve information in completely new ways. Knowledge representation has been appearing organically in key software applications through large R&D environments. Now with the introduction of our new modeling tool, we are providing an entry point for companies to begin to reap the rewards of this powerful new technology.”
This is the classic case of a press release that, laden with technical information and terminology, does little to position itself amongst the current set of offerings in the market. Any software that allows for interoperability will have a strong place in the market.
Megan Feil, January 04, 2013
January 3, 2013
Another partnership in the IT and knowledge management realm has been announced. Datamatics Global Services has decided to create a strategic alliance with TEMIS, a provider of semantic content enrichment solutions. We learned more about this alliance in the article from Semantic Web called “Datamatics Partners with TEMIS.”
As for existing clients, the Digital Publishing Solutions division at Datamatics offers next generation digital solutions to several top publishing houses around the world. The semantically enriched content solutions from TEMIS will enable users to intelligently work with and share increasing volumes of information.
Michael Thuleweit, Managing Director of Datamatics in Europe commented in the article:
“Semantically enriching content enhances the ability to discover, navigate and analyze the most relevant content. Today, this is an essential part of the modern digital publishing workflows. Through our partnership with TEMIS for semantic content enrichment, we will be able to help our customers attract new visitors, differentiate their products and also engage with them with a personalized experience.”
Semantic enrichment is an important aspect to a suite of technology tools that claims to be next-generation. It seems like the folks at Datamatics know what they are doing to strike up a partnership with such a company.
Megan Feil, January 03, 2013
December 10, 2012
Literary analysis meets big data analytics in the context of US politics. It’s a wild world we live in, but an important press release published by the Italian firm Expert System discussed the results of analysis on the language of the US presidential debates. “Obama Vs. Romney on Language: The Three Debates” breaks down the rhetoric into information on most used words and more.
Semantic and linguistic analysis was conducted by Expert System using the Cogito semantic platform to find that Romney used literally more words than Obama amounting to 14% percent more. As for word choice, Romney went for concepts with taxes, plans, programs, job, and America featured prominently. Obama’s most frequently used concept words were business and labor, but he was most often heard uttering the action verbs of do and make.
The article quoted Luca Scagliarini, VP Strategy & Business Development, Expert System:
“The upcoming elections in the U.S. have resulted in some very interesting analysis. This analysis focused only on the topics and concepts mentioned by the candidates, and while it is by no means a predictor, we believe that the semantic analysis of content will help anyone better understand and deal more effectively with any type of information.”
Obviously there would be no predictive value to this system. Knowing which words were mentioned more often than others by each candidate simply helps to inform voters about rhetoric, the impact of word choices and any potential values that could be extrapolated from this information.
Megan Feil, December 10, 2012
December 3, 2012
We would like to note a significant combination that took place in Austria: Semantic Web Company announced on their Web site that “Semantic Web Company and punkt. netServices Have Merged.” Both companies, the article notes, are prominent players in the European semantic Web arena. The press release informs us:
“In 2004 Semantic Web Company was founded as a spin off of punkt. netServices [founded in 2001] to bring the semantic web and linked data technologies closer to the needs of companies, consumers, and the government sector. We have done a lot of basic research those past years, as well as project-pioneering with prospective customers and partners. Finally we have consolidated our knowledge and skills in that field. What was avantgarde in 2004 now has become bleeding edge technology in present days. A good moment to join efforts and bring together the two sisters.”
The merger combines the companies’ experts in semantic Web services, information management, enterprise software architecture, search engines, collaboration software, and agile Web development. Facing the need fit all these folks into one place, the newly combined Semantic Web Company has taken this opportunity to move its headquarters to a Vienna building designed by the acclaimed early-twentieth-century architect Adolf Loos. (I’m officially jealous.) The firm serves clients in a number of different industries, including pharmaceutical, energy, communications, and finance.
Cynthia Murrell, December 03, 2012
November 27, 2012
Due to the ever increasingly globalized workforce, it is more important than ever that data analytics providers are able to appeal to a multitude of countries and languages and corner the polyglot market. Matthew Aslett of the Too Much Information blog recently reported on this topic in the article, “The Dawn of Polyglot Analytics.”
According to Aslett, the emergence of a polyglot analytics platform exemplifies a new approach to data analytics that is based on the user’s approach to analytics rather than the nature of the data.
The article states:
Polyglot analytics explains why we are seeing adoption of Hadoop and MapReduce as a complement to existing data warehousing deployments. It explains, for example, why a company like LinkedIn might adopt Hadoop for its People You May Know feature while retaining its investment in Aster Data for other analytic use cases. Polyglot analytics also explains why a company like eBay would retain its Teradata Enterprise Data Warehouse for storing and analyzing traditional transactional and customer data, as well as adopting Hadoop for storing and analyzing clickstream, user behaviour and other un/semi-structured data, while also adopting an exploratory analytic platform based on Teradata’s Extreme Data Appliance for extreme analytics on a combination of transaction and user behaviour data pulled from both its EDW and Hadoop deployments.
One company that is currently excelling in polyglot analytics is Polyspot. In the recent blog post, “Polyspot is Polyglot” we learned that Polyspot offers its services in over 50 languages. Language is no longer a hindrance to data management success. PolySpot warrants a close look. The company offers high value technology within the reach of most organizations’ budgets.
Jasmine Ashton, November 27, 2012
November 27, 2012
After Thomson Reuters bought ClearForest in 2007, some of its technology became the nifty open source project OpenCalais. The Cognifide blog offers some integration advice in “Adobe CQ5—OpenCalais Integration.”
The OpenCalais Web Service automatically incorporates semantic metadata into content. The best way to see what it does is to past a chunk of text, any text, into their Document Viewer. The tool will tease out and insert links for topics, social tags, entities (like organizations or industry terms), and events & facts. After you’ve played with that, check out the examples of ways the technology has been implemented on the Showcase page. It is acceptable to use the free OpenCalais for commercial purposes (the API key is obtainable here), but a Calais Professional version is available for power users.
Blogger and software engineer Mateusz Kula suggests a way to integrate OpenCalais with the Adobe CQ5 marketing cloud that makes automatic tagging a breeze. He writes:
“A fairly good way to integrate OpenCalais with CQ5 was to create a workflow step for content tagging that could be embedded into any workflow fired on some CQ event or by hand. The mentioned step pulls data internally from a page and calls the OpenCalais integration OSGi service.
Text data is collected from the fields of components lying on a page, then the integration service sends concatenated text to a web service and pulls tags back. Finally the workflow step adds nonexistent tags into the CQ tag manager ‘Calais’ namespace and applies tagging to a page.”
A helpful workflow diagram and configuration tips follow this explanation. Cognifide has created an integration package, which includes an example workflow to get you started. The final paragraph of the article includes a link you can use to download the package’s zipped folder.
Before they were snapped up by Thomson Reuters, ClearForest began in 1998 as an independent software start-up based in Tel Aviv, Israel. Marketing tech consulting firm Cognifide is located in London, UK. They are proud of the partnerships they have formed with Adobe and Sitecore.
Cynthia Murrell, November 27, 2012
October 22, 2012
Salesforce went social years ago. First, the company hired Steve Gilmore, a widely respected futurist and technology expert. Next, the company added various commenting and collaboration functions to the Salesforce platform. Now the company has taken the next logical step. Sentiment analysis has been added to the Salesforce Cloud Insights system.
The sentiment analysis capability answers such questions as:
- In a licensee’s content pool, what’s hot, what’s a problem, and what’s going right?
- How are customers’ sentiments trending over time or now?
- What customers are unhappy and why?
The Salesforce Marketing Cloud Command Center solution is the next generation of social engagement. By leveraging insights from the Marketing Cloud and more than 25 social analytics leaders, customers will derive deeper meaning from the millions of social conversations happening every day. The industry’s most comprehensive solution for managing social media engagement, the Social Command Center will provide customers with a new level of social media intelligence that will allow them to filter through the noise and quickly analyze large volumes of social data to generate actionable social intelligence and connect with customers in entirely new ways.
The engine for this innovative sentiment capability was developed by Bitext, based in Madrid, Spain. Unlike most companies, Bitext was designed to operate across languages. In one sense, Bitext approached semantic methods to operate without requiring the user to specify what language is being analyzed.
Bitext is a leading provider of OEM text analytics technology. Bitext develops semantic services for major European languages using a data-driven symbolic natural language processing system. Alongside integration into partner solutions including search, business intelligence and analytics, these services are available through two different channels: Bitext Consulting and the Bitext API, which provides a web service to open up the Bitext semantic technology to third-party developers.
As a result, Bitext Sentiment enables customers to harness the power of social intelligence and connect with customers in entirely new ways. Unlike the academic charts and often incomprehensible dashboards of confusing graphics, Bitext’s system outputs data which can be used to answer basic business questions quickly.
Any developer for Salesforce Marketing Cloud Insights or users of the system can tap the power of the unique Bitext innovations. Bitext Sentiment delivers multilingual sentiment analysis. The system is fueled by sophisticated semantic analysis. According to the founder of Bitext, Antonio Valderrabanos:
“We keep the technology behind the simple reports a business person or analyst needs. We focus on usability and delivering real time results, not confusion.”
Bitext’s system uncovers key insights or “info nuggets” from the millions of conversations that take place every day in social media.
He said in Madrid today:
Bitext can deliver information which can transform a company’s future. Our multilingual sentiment analysis in a real-time environment gives companies the opportunity to understand their customers better and faster than ever before.
Most of the systems asserting intelligence based sentiment analysis simply fail to handle most of the subtleties of human language. This is especially true of complex languages like Spanish or Portuguese and even more so when the Latin American varieties of these languages are considered. Our research revealed that Bitext Sentiment was built from the ground up using processing techniques designed to handle the complexity of natural language. Bitext represents morphological variation and syntactic analysis via its proprietary rule-based system, Bitext Sentiment capture nuances of meaning more effectively than other systems we have examined.
Bitext Sentiment allows an organization to gauge whether their customers have concerns about the message they are receiving or are reacting positively. Such focused, easily understood information allows users of the Bitext system to act swiftly to engage in the most effective manner.
Selected Features of Bitext Sentiment
Bitext Sentiment is a robust solution. Of particular interest to organizations seeking to leverage their “big data” from customer support and social media are:
Sentiment analysis that works using sophisticated rule-based language analysis to solve challenges such as identification of positive or negative words that do not relate to the brand in question and sentiment words that change their meaning when combined with other words
Entity extraction collects as a single Insight all of the brands, companies, people and so on that people have referred to positively or negatively, making it easy to see which are the most important subjects in a set of online conversations.
Entities context (brands, companies, people etc.) that have the strongest positive and negative sentiments are extracted into separate Insights, making it easy to compare brands, people or products and see the majority of positive or negative comments are directed.
The dictionaries and grammars that power Bitext Sentiment are built specifically for each language and language variety. Sentiment analysis is customized for each different language, not built with a one-size-fits-all technique.
The initial set of languages for Salesforce will be Spanish and Portuguese. All varieties of Spanish (Latin America and European) and Portuguese (Brazilian and European). Upon request, the system can support English, French, Italian, Catalan, Basque, Dutch and German. Other languages can be added as required.
Stephen E Arnold, October 22, 2012
Beyond Search, the “real” beyond search I might add
October 17, 2012
Cloud security for the enterprise needs improvement as many software vendors are beginning to provide their own cloud storage capabilities, and some companies are stepping up to the plate by offering new features. We learn in the article “Box Beefs Up Security and Search for Enterprise Storage” on GigaOM that search and content solution vendor Box is offering numerous new features including two-step authentication, company-wide search for administrators, and content scanning.
We learn about some of the new features in the article:
“Box is also offering new tools to let admins search across all enterprise content by parameters including user, content type and date range. Box users could always search across their own files, but this is universal search — using Box’s own search technology — across all a company’s users.
‘You can search across the whole organization for just video files that are saved in the last few days,’ [Box VP of marketing Robin ] Daniels said.”
Cloud storage can be an issue for companies which need to focus on security and manageability for compliance reasons; however, cloud security is an issue for search in general. Enterprise search still needs authentication capabilities and Intrafind’s ability to provide feature-rich solutions which include secure search, semantic linking, and sophisticated tagging creates a compliant and functional search environment within any organization.
Andrea Hayden, October 17, 2012