Ah, Ha. Search May Be Dying
January 18, 2016
I did not know that. I am delighted to have wisdom available from a blog focusing on search engine optimization.
Dear, old search. Are you really dying? I thought you had pulled off one of the Carlos Castaneda transmogrifications into augmented intelligence, customer support services, analytics, and my favorite Big Data. If Vivisimo can pull this off at IBM, almost any company with information access capabilities can wake up as a metasearch company and go to bed as a Big Data champ with the four Vs dancing in one’s dreams.
The write up points out:
Recent years have revealed a worrisome trend (for Google anyway) — search engine use overall has declined from 90 percent in 2009 to 86 percent in 2014. This might not seem like much of a downward trend, but if you consider that overall global Internet use has increased by 67 percent in the same period, that’s a lot of Internet users who aren’t turning to search.
The article represents this wonderful Pew Research chart:
But the section which tickled my Alphabet Google fancy was this passage:
There’s no denying that Google is the most complex searchable database on the Internet. It offers billions of results and is constantly innovating new ways to determine your search needs. However it would seem that Google’s impressive scope is the very thing that is sending people to apps and other websites to find the information they need. People want results that are personalized for them, while Google is busy trying to be everything for everyone. There are simply too many relevant results in Google’s database to match the personalization capabilities of apps and websites. That’s why apps are increasingly being used as research channels, especially among teens, who are 30 percent more likely to use them for search.
The inescapable conclusion seems to be that search is a goner.
I don’t agree, but that’s not germane to the SEO mavens who stand ready to serve customers eager for clicks, app downloads, and lots of SEO goodness.
At least the Mirror comes at the Alphabet Google thing with a bit of creativity. See, for example, “Google Slammed over Refusal to Advertise Plus Size Fashion to Curvy Consumers.” Now that’s real hard hitting evidence for the argument that search is on a down ward trajectory.
Stephen E Arnold, January 18, 2016
Stephen E Arnold
Surprise. News Corp. Thinks Probe of Google Is Okay
January 18, 2016
I love it when outfits which are engaged in real journalism comment about the Alphabet Google thing. Newspapers never had a monopolistic thought in their history. The newspaper wars are a myth. Yellow journalism was a result of color blind folks misunderstanding “real” data gathering and dissemination.
To learn more about News Corp.’s view of a Google anti trust probe, navigate to “News Corp. CEO Says Antitrust Probe of Google Could Be Warranted.” Yep, woulda, coulda, shoulda.
I learned:
Citing a lack of competition in the search market, especially in Europe, News Corp. CEO Robert Thomson called Monday for closer scrutiny of Google’s business by regulators.
I wonder if the News Corp. digital wizards is aware of:
- Exalead Search at https://www.exalead.com/search/
- Gibiru at https://anonymous-gibiru.com/
- Qwant at https://www.qwant.com/
- Silobreaker at http://www.silobreaker.com/
- Unbubble at https://www.unbubble.eu/
- Yandex at https://www.yandex.com/
There are some other services as well, but from the point of view of New Corp., they are probably irrelevant.
I assume that alternatives are not important to executives representing a company with an interesting track record in management and information gathering.
I wonder why folks are using the Alphabet Google thing? Thoughts, gentle reader?
Stephen E Arnold, January 18, 2016
AOL: A New Do for the Year of the Monkey
January 18, 2016
I read “AOL’s Identity Crisis: The Company May Ditch the AOL Brand.” I remember the flood of discs. I remember the hidden files thoughtfully placed on my hard drive when I installed America Online. I remember the Xoogler who bought his own local publishing outfit to reinvigorate AOL and, of course, his own local America Online. I remember Verizon buying AOL because, well, it could.
According to the write up:
one of AOL’s biggest priorities for the new year is figuring out its brand and investing in it, even if that means saying goodbye to the name “AOL” in favor of launching something completely new.
I learned that
Mark Ritson, a leading brand expert and marketing consultant, tells Business Insider that he also thinks the messy corporate brand definitely needs a clean up. AOL is tricky, he says, because it has very strong brand awareness, but that its image “has an unpalatable mix of being seen to be out of date and a business failure.”
No matter what name Verizon chooses, AOL will always evoke fond memories for me. The dial up modem, the chat groups, the fantastical email services.
So many memories. What ever happened to that Xoogler’s local news idea? Ah, it did not work out.
I look forward to the Yahooligans following AOL’s trajectory. Two new branding opportunities for the marketing consultants.
It is the year of the monkey too. Love those creatures.
Stephen E Arnold, January 18, 2016
DtSearch in the Cloud
January 18, 2016
Enterprise- and developer-search firm dtSearch now offers a platform for the cloud. PR.com informs us, “New .NET Solution Uses dtSearch with Microsoft Azure Files and RemoteApp.” The solution allows users to run the dtSearch engine entirely online with Microsoft Azure, ensuring their security with Microsoft’s RemoteApp. The press release elaborates:
“The solution enables cloud operation of all dtSearch components, leveraging Microsoft’s new Azure Files feature for dtSearch index storage. Searching (including all 25+ dtSearch search options) runs via Microsoft’s RemoteApp. Using RemoteApp gives the search component the ‘look and feel’ of a native application running under Windows, Android, iOS or OS/X. Developers using dtSearch’s core developer product, the dtSearch Engine, can find the solution on CodeProject, including complete Visual Studio 2015 .NET sample code.”
See the thorough write-up for many details about the product, including supported formats, search and classification options, and their terabyte indexer. We note, for example, the capacities for concurrent, multithreaded search and for federated searches with their dtSearch Spider.
Founded in 1991, dtSearch supplies search software to firms in several fields and to numerous government agencies around the world. The company also makes its products available for incorporation into other commercial applications. dtSearch has distributors worldwide, and is headquartered in Bethesda, Maryland.
Cynthia Murrell, January 18, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Machine Learning Hindsight
January 18, 2016
Have you ever found yourself saying, “If I only knew then, what I know now”? It is a moment we all experience, but instead of stewing over our past mistakes it is better to share the lessons we’ve learned with others. Data scientist Peadar Coyle learned some valuable lessons when he first started working with machine learning. He discusses three main things he learned in the article, “Three Things I Wish I Knew Earlier About Machine Learning.”
Here are the three items he wishes he knew then about machine learning, but know now:
- “Getting models into production is a lot more than just micro services
- Feature selection and feature extraction are really hard to learn from a book
- The evaluation phase is really important”
Developing models is an easy step, but putting them in production is difficult. There are many major steps that need attending to and doing all of the little jobs isn’t feasible on huge projects. Peadar recommends outsourcing when you can. Books and online information are good reference tools, but when they cannot be applied to actual situations the knowledge is useless. Paedar learned that real world experience has no comparison. When it comes to testing, it is a very important thing. Very much as real world experience is invaluable, so is the evaluation. Life does not hand perfect datasets for experimentation and testing different situations will better evaluate the model.
Paedar’s advice applies to machine learning, but it applies more to life in general.
Whitney Grace, January 18, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
AI News: Bad Links Resulted in My Finding This Smart Software Post
January 17, 2016
I followed some bad links and after a bit of poking around, I arrived at “A Tour of Machine Learning Algorithms.” The write up is more than two years old, but it does have some useful information to feed the hungry minds of the smart software crowd.
The write up explains machine learning algorithms group by learning style and by similarity. The brief explanations are helpful.
The major omission is that none of the algorithms apparently has any notable flaws or vulnerabilities. In our research, we found that the algorithms we tested could be manipulated by creating data which threw the method off the scent for accuracy.
One example is the flaw of a properly “trained” Bayesian system. By loading content outside the original training set’s scope, the Bayesian system happily generated off point results. This means that directed content injection such as shaped or weaponized blog posts or social media message flooding can make the systems wander.
Good news for those who want to manipulate smart software. Bad news for the decision makers who “assume’ the Bayesian system’s outputs remain on the mark.
Useful to know in my opinion. Descriptions of algorithms have to include their less sunny side, don’t you think?
Stephen E Arnold, January 17, 2016
Watson Weekly: Entrepreneurs, Watson Will Help You
January 17, 2016
I think that folks should help themselves. IBM is a giant struggling to generate revenues. The company’s approach to innovation is to buy companies which duplicate functions the firm already has. I assume that IBM’s senior executives ask Watson what to do, and s/he suggests, “Buy more companies like those you already own, pilgrim.”
I read “How IBM Watson Can Help Developers and Entrepreneurs with its Services”. I learned that
Technology giant IBM has been helping people from all walks of life,, especially developers who are prototyping and building Cloud-based cognitive computing applications, through Watson since its launch in 2011.
Okay, going on six years of helping.
Even better, IBM is now
allowing a growing ecosystem of developers, advertising professionals, businessmen, bankers, students, entrepreneurs, tech enthusiasts and people from various professions to use this advanced cognitive computing platform.
So who is being helped? IBM or the developers? The write up clears this up for me:
Kambhatla [An IBM cognitive computing wizard] described Watson Developer Cloud as one stop shop for developers. The developers can also bring their own data to many of the services, to help train Watson about a specific domain or industry and customize API models to speed up and simplify the development of cognitive apps. For instance, Watson can be used to help play relevant advertisements anywhere, be it shopping complex, roadside or amusement park based on image of people in the vicinity, as it can guess approximate age, gender, etc.
Okay, but it has been five years. Where’s the revenue? Let’s ask Watson. Okay, but I can’t find a public general purpose IBM Web site to allow that to happen.
Gee, maybe Watson’s advice is too darned good to make available to the addled goose? The PR folks obviously have access. The senior managers have access. Kambhatla has access. Why the shroud of unknowing, dear Big Blue?
Stephen E Arnold, January 17, 2016
Quote to Note: Newspaper Style
January 16, 2016
Wikipedia produces clicks for the search engines. Wikipedia allows students to output “essays” on almost any topic which catches the fancy of the common core crowd. Wikipedia also triggers some interesting comments about its approach.
Navigate to “Wikipedia: An Old-Fashioned Corner of Truth on the Internet.” The write up, which appears in an old fashioned newspaper, contains a quote to note. Here it is, gentle reader:
Because it was factual, updated quickly, and didn’t use that annoying newspaper style of trying to make stuff sensational. Wikipedia, the news source?
Annoying newspaper style? Great stuff. The write up about Wikipedia somewhat reluctantly points out that the service is useful.
I wonder if real journalists recycle Wikipedia information. What do you think? The tip off is the list of the strangest things found in Wikipedia.
Stephen E Arnold, January 16, 2016
The Key to Revenue? Ads. Predictive Analytics Not So Much
January 16, 2016
I read a darned amazing write up in a marketing blog. First, the story the marketing blog turned into “real news” is a sponsored study. That means an ad. But, even more interesting, the source of the funded study is a mid tier consulting firm. Now you know there are blue chip consulting outfits. I used to work at one and have done consulting projects for other blue chip outfits over the last 40 years. The blue chip outfits are more subtle in their thought leadership, which is one reason why there are blue chip outfits sitting on top of a pile of azure chips and gray chip vendors of expertise.
The second point is that the sponsored study conveniently converted into “real news” is that revenue comes from predicative analytics. Excuse me. But if a company is paid to flog an ad messages, doesn’t that mean the revenue comes from advertising or, in this case, clumsy propaganda. If the predictive analytics thing actually worked revenue wonders, wouldn’t the mid tier consulting firm use predictive analytics to generate cash? Wouldn’t the marketing newsletter use predictive analytics to generate cash?
To see this sponsored content daisy chain in action, navigate to “Forrester Report: Companies Using Predictive Analytics Make More Money.” The mid tier outfit in question is Forrester. Is their logo azure tinted? If not, maybe that is a color to consider. None of the stately expensive tie colors required.
The publication recycling the sponsored content as “real” news is Marketing Land. The name says it all, gentle reader.
What is the argument advanced for EverString by Forrester and Marketing Land?
Here’s the biggie:
The big takeaway: “Predictive marketing analytics use correlates with better business results and metrics.”
That is, compared with those in the survey who do not use predictive analytics (which it calls Retrospective Marketers). “Predictive Marketers,” the report notes, “are 2.9x more likely to report revenue growth at rates higher than the industry average.” They are also 2.1 times more likely to “occupy a commanding leadership position in the product/service markets they serve” and 1.8 times more likely to “consistently exceed goals when measuring the value their marketing organizations contribute to the business,” compared to the Retrospective Marketers in the survey. Forrester analyst Laura Ramos, who was involved in the report, told me the main point is clear: “Predictive analytics pays off.”
What froth? The 2.9x suggests real analysis. Sure, sure, I know about waves and magic squares.
There are companies delivering predictive analytics. Some of these outfits have been around for decades. Some of the methods have been known for centuries. I won’t remind you, gentle reader, about my wonky relative and his work for the stats guy Kolmogorov.
Suffice it to say that EverString paid Forrester. Forrester directly or indirectly smiled at Marketing Land. The reader learns that predictive analytics generate revenue.
Nope, the money comes from selling ads and, I assume, “influence.”
Put that in your algorithm and decide which is better: Selling ads or figuring out how to construct a predictive numerical recipe?
Right. Mid tier firms go the ad route. The folks recycling ads as news grab a ride on the propaganda unicycle.
Stephen E Arnold, January 16, 2016
Newspaper Reveals Tricks for Google Search
January 15, 2016
I love it when newspapers get into the online research game. I think fondly about the newspaper in Nevada. Its reporters were not able to figure out who owned the newspaper. Hint: Casino owner.
I read “How to Use Search Like a Pro: 10 Tips and Tricks for Google and Beyond.” The word “beyond” is darned popular when it comes to search. I wonder who has been using the phrase “beyond search” for a decade or more? Hmm. No idea.
The write up includes some jaw droppers for the folks who are not familiar with SDC Orbit or the conventions of Lockheed Dialog; for example:
Use quotes to search for a bound phrase. Okay. What happens when Google does not locate an exact phrase match? What then, gentle Guardian? No comment? Okay.
Here’s another tip and trick:
Use the OR operator. Now that is helpful when one is looking for a really big result set. How does one narrow a Google result set when the GOOG says, “About 1,400,000 results. Thoughts? Nope. Okay.
And one more. For the other seven you will have to read the source write up:
Use the “Related” operator to find more sites like — wait for it — the guardian.com. Nothing like using a dead tree publication to flog some clicks from the punters.
I wish to point out that the GOOG is deeply concerned about the decline in boat anchor type searches. The effort is being directed at providing information before the user knows s/he needs it. This is called predictive search.
I am delighted that the newspaper is describing how to use a search system which is losing traction. But, hey, that’s what makes real journalists and dead tree publishers the type of outfit that Jeff Bezos and Sheldon Adelson hungry to buy these companies.
Stephen E Arnold, January 15, 2016
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