February 28, 2017
The article on Sys-Con Media titled Delivering Comprehensive Intelligent Search examines the accomplishments of World Wide Technology (WWT) in building a better search engine for the business organization. The Enterprise Search Project Manager and Manager of Enterprise Content at WWT discovered that the average employee will waste over a full week each year looking for the information they need to do their work. The article details how they approached a solution for enterprise search,
We used the Gartner Magic Quadrants and started talks with all of the Magic Quadrant leaders. Then, through a down-selection process, we eventually landed on HPE… It wound up being that we went with the HPE IDOL tool, which has been one of the leaders in enterprise search, as well as big data analytics, for well over a decade now, because it has very extensible platform, something that you can really scale out and customize and build on top of.
Trying to replicate what Google delivers in an enterprise is a complicated task because of how siloed data is in the typical organization. The new search solution offers vast improvements in presenting employees with the relevant information, and all of the relevant information and prevents major time waste through comprehensive and intelligent search.
Chelsea Kerwin, February 28, 2017
February 28, 2017
We thought Google was left-leaning, but an article at the Guardian, “How Google’s Search Algorithm Spreads False Information with a Rightwing Bias,” seems to contradict that assessment. The article cites recent research by the Observer, which found neo-Nazi and anti-Semitic views prominently featured in Google search results. The Guardian followed up with its own research and documented more examples of right-leaning misinformation, like climate-change denials, anti-LGBT tirades, and Sandy Hook conspiracy theories. Reporters Olivia Solon and Sam Levin tell us:
The Guardian’s latest findings further suggest that Google’s searches are contributing to the problem. In the past, when a journalist or academic exposes one of these algorithmic hiccups, humans at Google quietly make manual adjustments in a process that’s neither transparent nor accountable.
At the same time, politically motivated third parties including the ‘alt-right’, a far-right movement in the US, use a variety of techniques to trick the algorithm and push propaganda and misinformation higher up Google’s search rankings.
These insidious manipulations – both by Google and by third parties trying to game the system – impact how users of the search engine perceive the world, even influencing the way they vote. This has led some researchers to study Google’s role in the presidential election in the same way that they have scrutinized Facebook.
Robert Epstein from the American Institute for Behavioral Research and Technology has spent four years trying to reverse engineer Google’s search algorithms. He believes, based on systematic research, that Google has the power to rig elections through something he calls the search engine manipulation effect (SEME).
Epstein conducted five experiments in two countries to find that biased rankings in search results can shift the opinions of undecided voters. If Google tweaks its algorithm to show more positive search results for a candidate, the searcher may form a more positive opinion of that candidate.
This does add a whole new, insidious dimension to propaganda. Did Orwell foresee algorithms? Further complicating the matter is the element of filter bubbles, through which many consume only information from homogenous sources, allowing no room for contrary facts. The article delves into how propagandists are gaming the system and describes Google’s response, so interested readers may wish to navigate there for more information.
One particular point gives me chills– Epstein states that research shows the vast majority of readers are not aware that bias exists within search rankings; they have no idea they are being manipulated. Perhaps those of us with some understanding of search algorithms can spread that insight to the rest of the multitude. It seems such education is sorely needed.
Cynthia Murrell, February 28, 2017
February 27, 2017
The article on InfoQ titled Amazon Introduces Rekognition for Image Analysis explores the managed service aimed at the explosive image market. According to research cited in the article, over 1 billion photos are taken every single day on Snapchat alone, compared to the 80 billion total taken in the year 2000. Rekognition’s deep learning power is focused on identifying meaning in visual content. The article states,
The capabilities that Rekognition provides include Object and Scene detection, Facial Analysis, Face Comparison and Facial Recognition. While Amazon Rekognition is a new public service, it has a proven track record. Jeff Barr, chief evangelist at AWS, explains: Powered by deep learning and built by our Computer Vision team over the course of many years, this fully-managed service already analyzes billions of images daily. It has been trained on thousands of objects and scenes. Rekognition was designed from the get-go to run at scale.
The facial analysis features include markers for image quality, facial landmarks like facial hair and open eyes, and sentiment expressed (smiling = happy.) The face comparison feature includes a similarity score that estimates the likelihood of two pictures being of the same person. Perhaps the most useful feature is object and scene detection, which Amazon believes will help users find specific moments by searching for certain objects. The use cases also span vacation rental markets and travel sites, which can now tag images with key terms for improved classifications.
Chelsea Kerwin, February 27, 2017
February 24, 2017
Intellisophic identifies itself as a Linkapedia company. Poking around Linkapedia’s ownership revealed some interesting factoids:
- Linkapedia is funded in part by GITP Ventures and SEMMX (possible a Semper fund)
- The company operates in Hawaii and Pennsylvania
- One of the founders is a monk / Zen master. (Calm is a useful characteristic when trying to spin money from a search machine.)
First, Intellisophic. The company describes itself this way at this link:
Intellisophic is the world’s largest provider of taxonomic content. Unlike other methods for taxonomy development that are limited by the expense of corporate librarians and subject matter experts, Intellisophic content is machine developed, leveraging knowledge from respected reference works. The taxonomies are unbounded by subject coverage and cost significantly less to create. The taxonomy library covers five million topic areas defined by hundreds of millions of terms. Our taxonomy library is constantly growing with the addition of new titles and publishing partners.
In addition, Intellisophic’s technology—Orthogonal Corpus Indexing—can identify concepts in large collections of text. The system can be sued to enrich an existing technology, business intelligence, and search. One angle Intellisophic exploits is its use of reference and educational books. The company is in the “content intelligence” market.
The company is described this way in Crunchbase:
Linkapedia is an interest based advertising platform that enables publishers and advertisers to monetize their traffic, and distribute their content to engaged audiences. As opposed to a plain search engine which delivers what users already know, Linkapedia’s AI algorithms understand the interests of users and helps them discover something new they may like even if they don’t already know to look for it. With Linkapedia content marketers can now add Discovery as a new powerful marketing channel like Search and Social.
Like other search related services, Linkapedia uses smart software. Crunchbase states:
What makes Linkapedia stand out is its AI discovery engine that understands every facet of human knowledge. “There’s always something for you on Linkapedia”. The way the platform works is simple: people discover information by exploring a knowledge directory (map) to find what interests them. Our algorithms show content and native ads precisely tailored to their interests. Linkapedia currently has hundreds of million interest headlines or posts from the worlds most popular sources. The significance of a post is that “someone thought something related to your interest was good enough to be saved or shared at a later time.” The potential of a post is that it is extremely specific to user interests and has been extracted from recognized authorities on millions of topics.
Interesting. Search positioned as indexing, discovery, social, and advertising.
Stephen E Arnold, February 24, 2017
February 24, 2017
Bad news, Google. The article titled Smartphone Apps Now Account for Half the Time Americans Spend Online on TechCrunch reveals that mobile applications are still on the rise. Throw in tablet apps and the total almost hits 60%. Google is already working to maintain relevancy with its In Apps feature for Androids, which searches inside apps themselves. The article explains,
This shift towards apps is exactly why Google has been working to integrate the “web of apps” into its search engine, and to make surfacing the information hidden in apps something its Google Search app is capable of handling. Our app usage has grown not only because of the ubiquity of smartphones, but also other factors – like faster speeds provided by 4G LTE networks, and smartphones with larger screens that make sitting at a desktop less of a necessity.
What apps are taking up the most of our time? Just the ones you would expect, such as Facebook, Messenger, YouTube, and Google Maps. But Pokemon Go is the little app that could, edging out Snapchat and Pinterest in the ranking of the top 15 mobile apps. According to a report from Senor Tower, Pokemon Go has gone beyond 180 million daily downloads. The growth of consumer time spent on apps is expected to keep growing, but comScore reassuringly states that desktops will also remain a key part of consumer’s lives for many years to come.
Chelsea Kerwin, February 24, 2017
February 24, 2017
We have good news and bad news for fans of government transparency. In their Secrecy News blog, the Federation of American Scientists’ reports, “Number of New Secrets in 2015 Near Historic Low.” Writer Steven Aftergood explains:
The production of new national security secrets dropped precipitously in the last five years and remained at historically low levels last year, according to a new annual report released today by the Information Security Oversight Office.
There were 53,425 new secrets (‘original classification decisions’) created by executive branch agencies in FY 2015. Though this represents a 14% increase from the all-time low achieved in FY 2014, it is still the second lowest number of original classification actions ever reported. Ten years earlier (2005), by contrast, there were more than 258,000 new secrets.
The new data appear to confirm that the national security classification system is undergoing a slow-motion process of transformation, involving continuing incremental reductions in classification activity and gradually increased disclosure. …
Meanwhile, ‘derivative classification activity,’ or the incorporation of existing secrets into new forms or products, dropped by 32%. The number of pages declassified increased by 30% over the year before.
A marked decrease in government secrecy—that’s the good news. On the other hand, the report reveals some troubling findings. For one thing, costs are not going down alongside classifications; in fact, they rose by eight percent last year. Also, response times to mandatory declassification requests (MDRs) are growing, leaving over 14,000 such requests to languish for over a year each. Finally, fewer newly classified documents carry the “declassify in ten years or less” specification, which means fewer items will become declassified automatically down the line.
Such red-tape tangles notwithstanding, the reduction in secret classifications does look like a sign that the government is moving toward more transparency. Can we trust the trajectory?
February 23, 2017
I noted “The Right Way to Search Posts on Reddit.” I find it interesting that the Reddit content is not comprehensively indexed by Google. One does stumble across this type of results list in the Google if one knows how to use Google’s less than obvious search syntax. Where’s bad stuff on Reddit? Google will reveal some links of interest to law enforcement professionals. For example:
Bing does a little better with certain Reddit content. To be fair, neither service is doing a bang up job indexing social media content but lists a fraction of the Google index pointers. For example:
So how does one search Reddit.com the “right way.” I noted this paragraph:
As of 2015, Reddit had accumulated over 190 million posts across 850,000 different subreddits (or communities), plus an additional 1.7 billion comments across all of those posts. That’s an incredible amount of content, and all of it can still be accessed on Reddit.
I would point out that the “all” is not accurate. There is a body of content deleted by moderators, including some of Reddit.com’s top dogs, which has been removed from the site.
Reddit offers some search syntax to help the researcher locate what is indexed by Reddit.com’s search system. The write up pointed to these strings:
- title:[text] searches only post titles.
- author:[username] searches only posts by the given username.
- selftext:[text] searches only the body of posts that were made as self-posts.
- subreddit:[name] searches only posts that were submitted to the given subreddit community.
- url:[text] searches only the URL of non-self-post posts.
- site:[text] searches only the domain name of non-self-post posts.
- nsfw:yes or nsfw:no to filter results based on whether they were marked as NSFW or not.
- self:yes or self:no to filter results based on whether they were self-posts or not.
The article contains a handful of other search commands; for example, Boolean and and or. How does one NOT out certain words. Use the minus sign. The word not is apparently minus sign appropriate for the discerning Reddit.com searcher.
Stephen E Arnold, February 23, 2017
February 22, 2017
Oh, the wonders of modern technology. Now, TechCrunch informs us, “This Amazing Search Engine Automatically Face Swaps You Into Your Image Results.” Searching may never be the same. Writer Devin Coldewey introduces us to Dreambit, a search engine that automatically swaps your face into select image-search results. The write-up includes some screenshots, and the results can be a bit surreal.
The system analyzes the picture of your face and determines how to intelligently crop it to leave nothing but your face. It then searches for images matching your search term — curly hair, for example — and looks for ‘doppelganger sets, images where the subject’s face is in a similar position to your own.
A similar process is done on the target images to mask out the faces and intelligently put your own in their place — and voila! You with curly hair, again and again and again. […]
It’s not limited to hairstyles, either: put yourself in a movie, a location, a painting — as long as there’s a similarly positioned face to swap yours with, the software can do it. A few facial features, like beards, make the edges of the face difficult to find, however, so you may not be able to swap with Rasputin or Gandalf.
Behind the nifty technology is the University of Washington’s Ira Kemelmacher-Shlizerman, a researcher in computer vision, facial recognition, and augmented reality. Her work could have more sober applications, too, like automated age-progressions to help with missing-person cases. Though the software is still in beta, it is easy to foresee a wide array of uses ahead. Now, more than ever, don’t believe everything you see.
Cynthia Murrell, February 22, 2017
February 20, 2017
How about point-and-click impulse buying? Sound good? Pinterest has merged looking at pictures with spending money for stuff.
Navigate to “Pinterest’s New ‘Lens’ IDs Objects and Helps You Buy Them.” I know that I spend hours looking at pictures on Pinterest. When I see wedding snapshots and notice a pair of shoes to die for, I can buy them with a click… almost. My hunch is that some children may find Pinterest buying as easy as Alexa Echo and Dot buying.
[Pinterest] announced a new feature called Lens, which will enable people to snap a picture of an item inside the Pinterest app. The app will then suggest objects it thinks are related. Think Shazam but for objects, not music. Surfacing the products will make it easier for people to take action, according to Pinterest. That could include everything from making a purchase to cooking a meal.
One of Pinterest’s wizards (Evan Sharp) allegedly said:
“Sometimes you spot something out in the world that looks interesting, but when you try to search for it online later, words fail you.” The new technology, Sharp said, “is capable of seeing the world the way you do.”
Isn’t the consumerization of no word search a life saver? Now I need a new gown to complement my size 11 triple E high heels. There’s a bourbon tasting in Harrod’s Creek next week, and I have to be a trend setter before we go squirrel hunting.
Stephen E Arnold, February 20, 2017
February 17, 2017
I read “Better Than Google: 7 Search Engines You Should Try.” I love that should. Very parental. Sometimes parents are wrong, however. I noted this passage:
There is no argument about Google being a reliable and popular search engine. But if you are interested in one that suits your specific interest, search type, or desire to help others, then check out these awesome seven alternatives.
I love that word awesome.
Okay, here are the sever search engines mom and dad want me to try out:
- Ixquick, now repositioned as StartPage
- Yahoo image search
- Lilo, which pops up an “add to Opera” link and reports that Opera is not supported. Interesting.
Not familiar with these. Well, you will find the research these deliver “awesome.”
I would point out that free Web search engines are struggling for traffic. In one of our HonkinNews’ programs we pointed out that DuckDuckGo “crowed” about having processed about 15 million queries in one day. Google fields billions in 24 hours.
For thorough research, it is often useful to check out such systems as Bing, Qwant, and Yandex. If one is looking with extreme prejudice, a dip into iseek.com, Giburu, or (heaven forbid) commercial services.
But awesome does not mean thorough. Awesome means a nifty view or a sense of apprehension and fear. Yep, that’s what I experience when I learn that I should try these search engines. Stirring.
Stephen E Arnold, February 17, 2017