German Music Analysis Engine Able to Compare and Sort Music into Genre
September 28, 2013
An article on Semanticweb.com titled German Engineers Developing a Semantic Music Analysis Engine reports on a project being undertaken in Germany that will allow for greater understanding of patterns and influences in music. The article takes Shakira as an example, explaining that the Franz Liszt Music Conservatory’s compilation will enable them to see the direct influence of traditional music on her pop music. In her case, a great amount of influence comes from Colombian slave music during the colonial-era. The article explains,
“For the past two years, Brazilian music ethnologists have been working together with other experts from Europe, Asia, Latin America and Africa on a semantic search engine that automatically recognises basic musical attributes such as tone and rhythm. ‘We are creating something that is independent of the global industry. The current search engines are only capable of finding identical musical pieces from huge databases,’ explained project worker Philip Kueppers. ‘We synthesize basic elements from rhythm in order to deliver general musical information to users.’
With more of an emphasis on music as opposed to artists themselves, there can be little to no confusion as to what category or genre a piece of music falls into. Ultimately the system is able to compare pieces of music in a way that until now was not possible. Of course this musical technology begs us to ask the question, would it work for business English?
Chelsea Kerwin, September 28, 2013
Sponsored by ArnoldIT.com, developer of Augmentext
Artificial Intelligence: Does Search Come Up Short?
September 21, 2013
In my view, artificial intelligence continues to capture attention. In actual use—particularly in search and content processing—AI evokes from me, “Aiiiiiiii.”
I read “The Unexpected Places Where Artificial Intelligence Will Emerge.” For investors who have pumped cash into various inventions that understand meaning, the article may surprise them. The future of AI is war, Google, Netflix, Amazon, spam, surveillance, robot space explorers, and financial trading.
The only challenge for AI is its lack of consistency. Smart systems work in certain circumstances and fail miserably in others. In my ISS lectures next week, I profile a number of systems which are alleged to be incredibly smart. The reality is that the systems are often rigged to generate expected outputs. The problem of “you don’t know what you don’t know” plagues the developers of these gee-whiz systems.
Will artificial intelligence improve search? Well, AI makes search easier for those who are happy to accept system outputs. For those who need to dig deeper, AI systems often produce results which do little to provide fine-grained detail or make it easy to identify suspect results.
For a good example of AI in action, look at Google search results when you are logged in. Examine Amazon recommendations closely. Better yet, watch the TV shows and films recommended for you by Netflix.
Stephen E Arnold, September 21, 2013
A Lament for the State of Analysis Tech in Economics
September 18, 2013
It seems like state-of-the-art analysis tools would be a priority in the data-rich field of finance. That’s why it is startling to learn that the technology being used by economic analysts and consultants seems to be stuck in the era of Windows 95. About Data shares a data-loving former economist’s lament in, “Bridging Economics and Data Science.”
Blogger Sam Bhagwat majored in economics because he was intrigued by innovative uses of data in that field; for example, a professor of his had gleaned conclusions about European patent law from a set of 19th century industrial-fair records. As he progressed, though, Bhagwat came to the disappointing realization that his field still relies on technology for which “outdated” is putting it mildly. He writes:
“When I graduated, the questions had changed, but the fundamental tools of analysis remained constant. Half of my classmates, including me, were headed to consulting or investment banking. These are ‘spreadsheet monkey’ positions analyzing client financial and operational data.
“In terms of relationship-building, this is great. Joining high strategy or high finance, you walk through the halls of power and learn to feel comfortable there. But in terms of technical skill-set, not so great. You begin to specialize in spreadsheets, a tool which hasn’t significantly improved since 1995.
“For someone like me, who wants to solve the most interesting problems out there, dealing with gigabytes and terabytes of data, realizing this was bitter medicine. Computational data analysis has changed a lot in the last twenty years, but my career track — economics, consulting, finance — hadn’t.”
So that is how one inquiring mind decided to make the leap from economics to data science. Bhagwat says he taught himself programming so he could pursue work he actually found challenging. I wonder, though—will he use his dual expertise to help bridge the gap between the two disciplines, or has he moved on, never to look back?
Cynthia Murrell, September 18, 2013
Sponsored by ArnoldIT.com, developer of Augmentext
Speeding Up Big Data With Platfora
September 18, 2013
Processing big data is slow and requires companies to depend heavily on their IT departments to compile reports. What if there was a way to make big data faster with a self-access system? Is someone programming castles in the sky? According to Info World, the answer is no and the article, “Platfora CEO: How We Deliver Sharper Analytics Faster” has some information that possibly verifies it. After a brief rundown of big data’s history, it gets to the interesting part that references how developers were not supposed to build data warehouses until they knew what question to ask their data. The problem is that questions change and analysts then cannot get the exact data they need.
Analysts and developers big challenges at the edge of big data: amount and type of data is growing at an exponential rate, nobody can know all the exact questions they need to ask in advance, maintain competiveness, and answer unanticipated questions. The biggest item the article claims analysts need is self-service.
Platfora then steps up to the bat with its new business intelligence platform:
“The integrated platform we developed to support a new era of self-service analytics helps to remove the obstacles to business intelligence described earlier by enabling an “interest-driven pipeline” of data controlled by the end-user. The end-user — typically a business analyst — can access raw data directly from Hadoop, which is then transformed into interactive, in-memory business intelligence. There is no need for a data warehouse or for separate ETL (extract, transfer, load) software and the headaches described above.”
Self-empowerment and the ability to find new data patterns all on your own. Are we seeing the next big data phase? Platfora is making analytics “sharp.” Cue the ZZ Top music.
Whitney Grace, September 18, 2013
Sponsored by ArnoldIT.com, developer of Beyond Search
Anonymizing Writing Style
September 11, 2013
Author J.K. Rowling recently learned firsthand how sophisticated analytics software has become. It was a linguistic analysis of the text in The Cuckoo’s Calling‘s which unmasked her as the popular crime-novel’s author “Robert Galbraith.” (These tools were originally devised to combat plagiarism.) Now, I Programmer tells us in “Anonymouth Hides Identity,” open-source software is being crafted to foil such tools, and give writers “stylometric anonymity.”
Whether a wordsmith just wants to enjoy a long-lost sense of anonymity, as the wildly successful author of the Harry Potter series attempted to do, or has more high-stakes reasons to hide behind a pen name, a team from Drexel University has the answer. The students from the school’s Privacy, Security, and Automation Lab (PSAL) just captured the Andreas Pfitzmann Best Student Paper Award at this year’s Privacy Enhancing Technologies Symposium for their paper on the subject. The article reveals:
The idea behind Anonymouth is that sylometry can be a threat in situations where individuals want to ensure their privacy while continuing to interact with others over the Internet. A presentation about the program cites two hypothetical scenarios:
*Alice the Anonymous Blogger vs.Bob the Abusive Employer
*Anonymous Forum vs. Oppressive Government. . . .
The JStylo-Anonymouth (JSAN) framework is work in progress at PSAL under the supervision of assistant professor of computer science, Dr. Rachel Greenstadt. It consists of two parts:
*JStylo – authorship attribution framework, used as the underlying feature extraction employing a set of linguistic features
*Anonymouth – authorship evasion (anonymization) framework, which suggests changes that need to be made.
The admittedly very small study discussed in the paper found that 80 percent of participants were able to produce anonymous documents “to a limited extent.” It also found certain constraints– it was more difficult to anonymize existing documents than new creations, for example. Still, this is an interesting development, and I am sure we will see more efforts in this direction.
Cynthia Murrell, September 11, 2013
Sponsored by ArnoldIT.com, developer of Augmentext
Sorting Through Big Data the Right Way with Web Analytics
September 11, 2013
On B2C, an article titled 5 Web Analytics Truths for Smart Digital Marketing mentions different approaches to finding the relevant data for your business. The first suggestion is catering to the staff on hand. People at different levels have different focuses, and an open conversation about what they want to learn from the data at hand might be invaluable. At the same time, how you view the data in powerful tools such as Google Analytics can make all the difference to the impression it makes on you. The article explains,
“Today’s analytics platforms… are very powerful and allow us the ability to go beyond simplistic hit collection, and really dive into rich data and patterns. You can easily report and derive insights with visitor segmentation, have quick visibility into buyer or non-buyer behavior, group content by asset type, measure gated or ungated content consumption, and relatively easily run a cohort analysis. These are just a few views that could be utilized when segmenting your data.”
Another piece of advice is to optimize while tracking everything you can. Keeping technology up to date is imperative, yes, but only if you are using it to its full potential. Altogether, the article provides a handful of the painful truths about the reality of smart digital marketing.
Chelsea Kerwin, September 11, 2013
Sponsored by ArnoldIT.com, developer of Augmentext
Avoid Being Red Queened: How to Run Ahead of Social Media Competition
September 10, 2013
The article Using Social Analytics and BI to be a Smarter Social Business on Don’t Mind Rick builds an elaborate metaphor between Social Analytics and Alice in Wonderland. The Red Queen Effect, as the article discusses, refers to those companies that are simply running to keep in the same place. The article encourages companies to avoid this.
“If you are using Social Media data just for history based predictions you are doing yourself a disservice. You now can know what your customer is thinking since they share their thoughts on social media. What your customer is doing, since they share their activities on social media. And you can know what your customer wants, since he is also sharing this on social media”
Of course, this dredges up the inevitable fear of being creepy. For example, Target sending out catalogues to a pregnant woman based on purchase patterns before the woman even told her family. The article also brings up the buzzword web care, or companies responding mainly to negative feedback on social media. Instead of this, the article suggests allowing trial runs of products, since what is a better test of whether you like something than trying it out yourself? At the least, the article is a remarkable collection of social media and business buzzwords.
Chelsea Kerwin, September 10, 2013
Sponsored by ArnoldIT.com, developer of Augmentext
Enterprise Search: Finding Flounders Floundering
September 9, 2013
A founder is a flat fish. In today’s whiz kid world, “flounder” does not make one drool for a fish stew. “Flounder” means to the Free Dictionary, “to move or act clumsily and in confusion.” I made the connection to search as a result of a seemingly innocuous discussion on LinkedIn about improving search.
A flounder not yet out of water.
I am not sure about the rules for linking to LinkedIn content. I have to watch my Ps and Qs because two of the goslings and I learned on Friday, September 6, 2013, that some of the queries I launched from my research computer were not processed by Slideshare. Was this a glitch or some intentional action? I don’t know. To be on the safe side, I will not link to the thread called “How to manage queries having no relevant answers but still matching some terms.” If you are a LinkedIn customer, you can log in and locate the discussion using the LinkedIn “finding” system. How well with that work out for you? Well, that’s another search topic.
To recap the thread, a LinkedIn customer is responsible for an Intranet search system. When its users run a query, the system produces a results list which do not answer some users’ questions. There is term matching, but the content is not on point. I no longer like to beat the drum for precision and recall. We are now in the era of good enough search. Few take the time to create a vetted content inventory. When the search system is rolled out, no one really knows what’s “in” the index. The point that a query contains terms which match some content but makes users grouse is not new.
Caught by an unhappy user who happens to be the CFO figuring out why so much money was spent for a search system that did not work.
The fix, of course, is like trying to refuel an old fashioned propeller driven aircraft with a somewhat more modern jet powered tanker. The job is going to be tricky and may end with some excitement. Jets and prop driven aircraft like enterprise search and quick mixes might not be a happy combination like peanut butter and jelly.
In 2004, then Googler Dave Girouard said in eCommerce Times:
“The funny part is it’s easier to find box scores from the 1957 World Series than it is to find last quarter’s sales presentation in the enterprise. While Web search has gotten really good, enterprise search has stagnated, and that’s why we really believe it’s a problem that needs to be solved and that Google has a unique set of capabilities to solve it.”
Well, Mr. Girouard has moved on and Google is advertising on LinkedIn for yet another wizard to work on enterprise search. If Google cannot knock the ball out of the park, who can? Is HP Autonomy the go-to system? What about a low-cost option like dtSearch? Why not download Elasticsearch, Constellio, of one of the other open source solutions? Maybe a company should embrace a predictive solution from Agilex or Palantir?
Attensity: Pumping Up Effort in Europe?
September 7, 2013
“Steinbrück gewinnt TV-Duell im Netz haushoch” reported that Attensity identified more negative answers in a televised debate. Who were the debaters? Angela Merkel and Peer Steinbrrück. Like many US political debates, the Wirtschafts Woche report suggested there was no clear winner.
What I find interesting is that Attensity is using its methods to analyze political debates in Germany as a marketing tactic. I just returned from Europe, and I formed the opinion that the economy of Germany and a some other large European countries was not exactly in turbo-charge mode.
Will Attensity close deals with this approach to marketing? I don’t know, but if Attensity does book some big deals with data analysis, I anticipate a rush of me-too efforts.
Unfortunately, the analyses by Attensity and others are only able to support the no clear winner conclusion. Is this a common problem of next generation analytics programs?
I address some of these issues in my ISS lecture in late September. See the ISS program for more information.
IBM Lands New Account with Reevoo
September 5, 2013
Merchants at the U.K.’s the Jewellery Channel will soon have new analytics tools at their fingertips. PRWeb reveals the deal in the lengthily titled, “Reevoo and IBM Help the Jewellery Channel Analyse Customer Sentiment to Engage Customers and Build Trust.” Reevoo has embedded IBM’s Content Analytics with Enterprise Search into their Insight platform, which underpins the sparkly retail site. The press release informs us:
“The Jewellery Channel can leverage the sophisticated capabilities of IBM Content Analytics to access, aggregate and analyze unstructured content, understanding the meaning and context of human language within textual information found in both internal and external sources.
“The sentiment and natural language processing performed by Reevoo Insight with IBM Content Analytics not only unveils trends, patterns, issues and opportunities but also quickly identifies the root causes of why key metrics are changing. All the results are then made available through a series of user-friendly, visual actionable insights, customized for different roles.”
IBM has developed its Smarter Commerce program, of which its Content Analytics is a part, to help customers adapt to today’s dynamic tech landscape. The idea is to put the customer front-and-center, and IBM has tailored solutions for the fields of banking, electronics, consumer products, retail, and communications.
Based in London, social-commerce firm Reevoo was launched in 2005. Its cloud-based services aim to tap into social-media sentiment to provide clients with actionable insights. They pride themselves on their unique, flexible model, which they say outperforms the industry standard by far.
Cynthia Murrell, September 05, 2013
Sponsored by ArnoldIT.com, developer of Augmentext
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