September 22, 2015
There is a new tool out to help companies compile information on their competitors: RivalSeek. This brainchild of entrepreneur Richard Brevig seeks to combat an issue he encountered when he turned to Google while researching the market for a different project: Google’s “personalized search” filters
keep users from viewing the whole landscape of any particular field. Frustration led Brevig to develop some tools of his own, which he realized might appeal to others. The site’s homepage explains simply:
“Find your competitors that Google can’t. RivalSeek’s competitor search engine looks past filter bubbles, finding competitors you’ve never heard of.”
More information can be found in Brevig’s brief introductory video on YouTube. There’s also this “quick demo,” which can be found on YouTube or playing quietly on RivalSeek’s home page. While the tool is still in Beta, Brevig is confident enough in its usefulness to charge $29 a month for access. You can find an example success story, for the Dollar Shave Club, at the company’s blog.
This is a great idea. While Google’s filter bubbles can be convenient, it is clear that confirmation bias is not their only hazard. Perhaps Brevig would be interested in expanding this tool into other areas, like science, literature, or sociology. Just a suggestion.
Cynthia Murrell, September 22, 2015
September 18, 2015
We’ve learned of an interesting alliance from this announcement at OpenPR, “Strategic Partnership Between Wabion and Twigkit in the Enterprise Search Sector.” We predict that more and fancier interfaces will arise from this deal. Wabion works closely with Google, and was named “top Google for Work Partner” in the DACH (Germany, Austria, and Switzerland) region. Now the company will bring TwigKit’s user-experience prowess to their enterprise search offerings. The press release notes:
“By providing simple building blocks for traditionally complex problems, Twigkit strikes the perfect balance between out of the box experience and fine-grained control for GSA applications. Twigkit delivers customised, elegant, search-based applications that can be delivered in a fraction of the time when compared to bespoke development. The resulting applications delivers demonstrably better results and have been proven in the most demanding scenarios. The outcome is not just a better and more efficient experience for both administrators and users alike but the opportunity to allow businesses to realise the value of their information outside of the standard keyword search and list of results approach.”
Twigkit is excited for this chance to expand into the German-speaking market, while Wabion looks forward to providing a richer UI within the Google Search Appliance.
Founded in 2009, Twigkit splits its operations between Cambridge, UK, and Milpitas, California. As of this writing, they are looking to hire some developers and engineers. The Wabion Group maintains offices in Germany and Austria, and was founded in 2011. They are currently seeking one developer to fill a vacancy in Switzerland.
Cynthia Murrell, September 18, 2015
September 16, 2015
What never ceases to amaze me is that people are always perplexed when goals for technology change. It always comes with a big hullabaloo and rather than complaining about the changes, time would be better spent learning ways to adapt and learn from the changes. Enterprise search is one of those technology topics that sees slow growth, but when changes occur they are huge. Digital Workplace Group tracks the newest changes in enterprise search, explains why they happened, and how to adapt: “7 Ways The Goal Posts On Enterprise Search Have Moved.”
After spending an inordinate amount of explaining how the author arrived at the seven ways enterprise search has changed, we are finally treated to the bulk of the article. Among the seven reasons are obvious insights that have been discussed in prior articles on Beyond Search, but there are new ideas to ruminate about. Among the obvious are that users want direct answers, they expect search to do more than find information, and understanding a user’s intent. While the obvious insights are already implemented in search engines, enterprise search lags behind.
Enterprise search should work on a more personalized level due it being part of a closed network and how people rely on it to fulfill an immediate need. A social filter could be applied to display a user’s personal data in search results and also users rely on the search filter as a quick shortcut feature. Enterprise search is way behind in taking advantage of search analytics and how users consume and manipulate data.
“To summarize everything above: Search isn’t about search; it’s about finding, connecting, answers, behaviors and productivity. Some of the above changes are already here within enterprises. Some are still just being tested in the consumer space. But all of them point to a new phase in the life of the Internet, intranets, computer technology and the experience of modern, digital work.”
As always there is a lot of room for enterprise search improvement, but these changes need to made for an updated and better work experience.
September 10, 2015
Elasticsearch is one of the top open source search engines and is employed by many companies including Netflix, Wikipedia, GitHub, and Facebook. Elasticsearch wants to get a foothold into the Japanese technology market. We can assume, because Japan is one of the world’s top producers of advanced technology and has a huge consumer base. Once a technology is adopted in Japan, you can bet that it will have an even bigger adoption rate.
The company has launched a Japanese promotional campaign and a uploaded video entitled “Elasticsearch Product Video” to its YouTube channel. The video comes with Japanese subtitles with appearances by CEO Steven Schuurman, VP of Engineering Kevin Kluge, Elasticsearch creator Shay Bannon, and VP of Sales Justin Hoffman. The video showcases how Elasticsearch is open source software, how it has been integrated into many companies’ frameworks, its worldwide reach, product improvement, as well as the good it can do.
Justin Hoffman said that, “I think the concept of an open source company bringing a commercial product to market is very important to our company. Because the customers want to know on one hand that you have the open source community and its evolution and development at the top of your priority list. On the other hand, they appreciate that you’re innovating and bringing products to market that solve real problems.”
It is a neat video that runs down what Elasticsearch is capable of, the only complaint is that bland music in the background. They could benefit from licensing the Jive Aces “Bring Me Sunshine” it relates the proper mood.
September 10, 2015
An article at WT Vox announces, “Google Is Working on a New Type of Algorithm Called ‘Thought Vectors’.” It sounds like a good use for a baseball cap with electrodes, a battery pack, WiFi, and a person who thinks great thoughts. In actuality, it’s a project based on the work of esteemed computer scientist Geoffrey E. Hinton, who has been exploring the idea of neural networks for decades. Hinton is now working with Google to create the sophisticated algorithm of our dreams (or nightmares, depending on one’s perspective).
Existing language processing software has come a very long way; Google Translate, for example, searches dictionaries and previously translated docs to translate phrases. The app usually does a passably good job of giving one the gist of a source document, but results are far from reliably accurate (and are often grammatically comical.) Thought vectors, on the other hand, will allow software to extract meanings, not just correlations, from text.
Continuing to use translation software as the example, reporter Aiden Russell writes:
“The technique works by ascribing each word a set of numbers (or vector) that define its position in a theoretical ‘meaning space’ or cloud. A sentence can be looked at as a path between these words, which can in turn be distilled down to its own set of numbers, or thought vector….
“The key is working out which numbers to assign each word in a language – this is where deep learning comes in. Initially the positions of words within each cloud are ordered at random and the translation algorithm begins training on a dataset of translated sentences. At first the translations it produces are nonsense, but a feedback loop provides an error signal that allows the position of each word to be refined until eventually the positions of words in the cloud captures the way humans use them – effectively a map of their meanings.”
But, won’t all efficient machine learning lead to a killer-robot-ruled dystopia? Hinton bats away that claim as a distraction; he’s actually more concerned about the ways big data is already being (mis)used by intelligence agencies. The man has a point.
Cynthia Murrell, September 10, 2015
September 4, 2015
The Dark Web is not only used to buy and sell illegal drugs, but it is also used to perpetuate sex trafficking, especially of children. The work of law enforcement agencies working to prevent the abuse of sex trafficking victims is detailed in a report by the Australia Broadcasting Corporation called “Secret ‘Dark Net’ Operation Saves Scores Of Children From Abuse; Ringleader Shannon McCoole Behind Bars After Police Take Over Child Porn Site.” For ten months, Argos, the Queensland, police anti-pedophile taskforce tracked usage on an Internet bulletin board with 45,000 members that viewed and uploaded child pornography.
The Dark Web is notorious for encrypting user information and that is one of the main draws, because users can conduct business or other illegal activities, such as view child pornography, without fear of retribution. Even the Dark Web, however, leaves a digital trail and Argos was able to track down the Web site’s administrator. It turned out the administrator was an Australian childcare worker who had been sentenced to 35 years in jail for sexually abusing seven children in his care and sharing child pornography.
Argos was able to catch the perpetrator by noticing patterns in his language usage in posts he made to the bulletin board (he used the greeting “hiya”). Using advanced search techniques, the police sifted through results and narrowed them down to a Facebook page and a photograph. From the Facebook page, they got the administrator’s name and made an arrest.
After arresting the ringleader, Argos took over the community and started to track down the rest of the users.
” ‘Phase two was to take over the network, assume control of the network, try to identify as many of the key administrators as we could and remove them,’ Detective Inspector Jon Rouse said. ‘Ultimately, you had a child sex offender network that was being administered by police.’ ”
When they took over the network, the police were required to work in real-time to interact with the users and gather information to make arrests.
Even though the Queensland police were able to end one Dark Web child pornography ring and save many children from abuse, there are still many Dark Web sites centered on child sex trafficking.
August 28, 2015
The article on Funnelback titled Five Ways to Improve Your Website Search offers tips that may seem obvious, but could always stand to be reinforced. Sometimes the Google site:<url> is not enough. The first tip, for example, is simply to be helpful. That means recognizing synonyms and perhaps adding an autocomplete function in case your site users think in different terms than you do. The worst case scenario is search is typing in a term and yielding no results, especially when the problem is just language and the thing being searched for is actually present, just not found. The article goes into the importance of the personal touch as well,
“You can use more than just the user’s search term to inform the results your search engine delivers… For example, if you search for ‘open day’ on a university website, it might be more appropriate to promote and display an ‘International Open Day’ event result to prospective international students instead of your ‘Domestic Student Open Day’ counterpart event. This change in search behavior could be determined by the user’s location – even if it wasn’t part of their original search query.”
The article also suggests learning from the search engine. Obviously, analyzing what customers are most likely to search for on your website will tell you a lot about what sort of marketing is working, and what sort of customers you are attracting. Don’t underestimate search.
Chelsea Kerwin, August 28, 2015
August 27, 2015
The article on Life Hacker titled TUN’s Textbook Search Engine Compares Prices from Thousands of Sellers reviews TUN, or the “Textbook Save Engine.” It’s an ongoing issue for college students that tuition and fees are only the beginning of the expenses. Textbook costs alone can skyrocket for students who have no choice but to buy the assigned books if they want to pass their classes. TUN offers students all of the options available from thousands of booksellers. The article says,
“The “Textbook Save Engine” can search by ISBN, author, or title, and you can even use the service to sell textbooks as well. According to the main search page…students who have used the service have saved over 80% on average buying textbooks. That’s a lot of savings when you normally have to spend hundreds of dollars on books every semester… TUN’s textbook search engine even scours other sites for finding and buying cheap textbooks; like Amazon, Chegg, and Abe Books.”
After typing in the book title, you get a list of editions. For example, when I entered Pride and Prejudice, which I had to read for two separate English courses, TUN listed an annotated version, several versions with different forewords (which are occasionally studied in the classroom as well) and Pride and Prejudice and Zombies. After you select an edition, you are brought to the results, laid out with shipping and total prices. A handy tool for students who leave themselves enough time to order their books ahead of the beginning of the class.
Chelsea Kerwin, August 27, 2015
August 27, 2015
Sit back and absorb this article’s title for a moment: big data vendors don’t understand big data. How can IT vendors not understand one of the IT industry’s largest selling products? According to Computing, “SAP, Oracle, and HP ‘Don’t Get’ Big Data, Claims Massive Analytic Chairman” in a very bold statement.
Executive chairman and founder of the Oscar AP platform George Frangou claims that companies that like Oracle, HP, and SAP do not know how to help their customers take advantage of their big data and are more interested in getting customers hooked into their ecosystems than providing true analytical insight.
One of the reasons Frangou says this is because his Oscar AP is more “advanced” and allows users to foretell the future with various outcomes. The Oscar AP platform is part of the next round of big data called massive analytics. HP, Oracle, and SAP cannot wrap their heads around massive analytics yet, because they are more concerned with selling their product.
“Because of this, Frangou said Massive Analytic is ‘quite unashamedly following a displacement strategy to displace the incumbents because they’re not getting it.’ He added that SAP HANA, Oracle Exalytics and HP Haven are essentially the same product because they’re built on the same base code.”
Frangou went on to say that big data customers are spending more money than they need to and are getting sucked into purchasing more products in order to make their big data plans work. It appears to be a vicious cycle. Frangou said that cloud analytics are the best option for customers and to go with SAP, although still more barriers remain getting a decent cloud analytics platform off the ground.
It does not come as surprising that big data products are falling short of their promised results. A similar comparison would be the Windows OS falling well below expected desired performance expectations and users spending way too much time troubleshooting than getting their projects done.
August 18, 2015
In conversations surrounding enterprise software, the on-site vs. cloud debate is not a new one. However, it is one that is heating up. Microsoft’s announcements relating to SharePoint Server 2016 and its continued support for on-premises infrastructure definitely stoke the fires of that conversation. CIO takes on the debate in their article, “Why SharePoint is the Last Great On-Premises Application.”
The article begins:
“While it seems like almost every piece of IT is moving to cloud these days, there are still plenty of reasons to keep SharePoint in your server room – where it belongs . . . SharePoint Server is such a sticky product with tentacles everywhere in the enterprise that it may well be the last great on-premises application. Let’s explore why.”
The article goes on to delineate many reasons why on-site is still favored among IT professionals. Only time will tell if the cloud really is able to completely take over, or if the market will demand continued access to on-site solutions. Until the verdict is clear, stay on top of the latest updates on both sides of the aisle with ArnoldIT.com. Stephen E. Arnold is a lifelong leader in search, and his dedicated SharePoint feed is of particular value for SharePoint professionals.
Emily Rae Aldridge, August 18, 2015