Google Introduces Fact Checking Tool
October 26, 2016
If it works as advertised, a new Google feature will be welcomed by many users—World News Report tells us, “Google Introduced Fact Checking Feature Intended to Help Readers See Whether News Is Actually True—Just in Time for US Elections.” The move is part of a trend for websites, who seem to have recognized that savvy readers don’t just believe everything they read. Writer Peter Woodford reports:
Through an algorithmic process from schema.org known as ClaimReview, live stories will be linked to fact checking articles and websites. This will allow readers to quickly validate or debunk stories they read online. Related fact-checking stories will appear onscreen underneath the main headline. The example Google uses shows a headline over passport checks for pregnant women, with a link to Full Fact’s analysis of the issue. Readers will be able to see if stories are fake or if claims in the headline are false or being exaggerated. Fact check will initially be available in the UK and US through the Google News site as well as the News & Weather apps for both Android and iOS. Publishers who wish to become part of the new service can apply to have their sites included.
Woodford points to Facebook’s recent trouble with the truth within its Trending Topics feature and observes that many people are concerned about the lack of honesty on display this particular election cycle. Google, wisely, did not mention any candidates, but Woodford notes that Politifact rates 71% of Trump’s statements as false (and, I would add, 27% of Secretary Clinton’s statements as false. Everything is relative.) If the trend continues, it will be prudent for all citizens to rely on (unbiased) fact-checking tools on a regular basis.
Cynthia Murrell, October 26, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
HonkinNews for 25 October 2016 Now Available
October 25, 2016
This week’s video roundup of search, online, and content processing news is now available. Navigate to this link for seven minutes of plain talk about the giblets and goose feathers in the datasphere. This week’s program links Google’s mobile search index with the company’s decision to modify its privacy policies for tracking user actions. The program includes an analysis of Marissa Mayer’s managerial performance at Yahoo. Better browser history search swoops into the program too. Almost live from Harrod’s Creek in rural Kentucky. HonkinNews is semi educational, semi informative, and semi fun. Three programs at the end of the year will focus on Stephen E Arnold’s three monographs about Google.
Kenny Toth, October 25, 2016
Falcon Searches Through Browser History
October 21, 2016
Have you ever visited a Web site and then lost the address or could not find a particular section on it? You know that the page exists, but no matter how often you use an advanced search feature or scour through your browser history it cannot be found. If you use Google Chrome as your main browser than there is a solution, says GHacks in the article, “Falcon: Full-Text history Search For Chrome.”
Falcon is a Google Chrome extension that adds full-text history search to a browser. Chrome usually remembers Web sites and their extensions when you type them into the address bar. The Falcon extension augments the default behavior to match text found on previously visited Web Sites.
Falcon is a search option within a search feature:
The main advantage of Falcon over Chrome’s default way of returning results is that it may provide you with better results. If the title or URL of a page don’t contain the keyword you entered in the address bar, it won’t be displayed by Chrome as a suggestion even if the page is full of that keyword. With Falcon, that page may be returned as well in the suggestions.
The new Chrome extension acts as a delimiter to recorded Web history and improves a user’s search experience so they do not have to sift through results individually.
Whitney Grace, October 21, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Quote to Note: Enterprise Search As a Black Hole
October 19, 2016
Here’s a quote to note from “Slack CEO Describes Holy Grail of Virtual Assistants.” Slack seeks to create smart software capable of correlating information from enterprise applications. Good idea. The write up says:
Slack CEO Stewart Butterfield has an audacious goal: Turning his messaging and collaboration platform into an uber virtual assistant capable of searching every enterprise application to deliver employees pertinent information.
Got it. Employees cannot locate information needed for their job. Let me sidestep the issue of hiring people incapable of locating information in the first place.
Here’s the quote I noted:
And if Slack succeeds, it could seal the timeless black hole of wasted productivity enterprise search and other tools have failed to close.
I love the “timeless black hole of wasted productivity of enterprise search.” Great stuff, particularly because outfits like Wolters Kluwer continue to oscillate between proprietary search investments like Qwant.com and open source solutions like Lucene/Solr.
Do organizations create these black holes or is software to blame? Information is a slippery fish, which often find “timeless black holes” inhospitable.
Stephen E Arnold, October 19, 2016
HonkinNews for October 18, 2016 Now Available
October 18, 2016
From the wilds of rural Kentucky, Stephen E Arnold highlights the week’s search, online, and content processing news. Two services make it easy to buy a product with a mouse click. Will Amazon’s eCommerce business be threatened by eBay and Pinterest? Plus, this week’s program comments about Google and Pindrop, National Geographic’s new topographic maps, and another of Yahoo’s mounting public relations challenges. The program explains that Google is taking a step toward marginalizing the “regular” Web in favor of the mobile Web. You can view the video shot in eight millimeter film from a cabin in a hollow at this link.
Kenny Toth, October 18, 2016
Artificial Intelligence Is Only a Download Away
October 17, 2016
Artificial intelligence still remains a thing of imagination in most people’s minds, because we do not understand how much it actually impacts our daily lives. If you use a smartphone of any kind, it is programmed with software, apps, and a digital assistant teeming with artificial intelligence. We are just so used to thinking that AI is the product of robots that we are unaware our phones, tablets, and other mobiles devices are little robots of their own.
Artificial intelligence programming and development is also on the daily task list on many software technicians. If you happen to have any technical background, you might be interested to know that there are many open source options to begin experimenting with artificial intelligence. Datamation rounded up the “15 Top Open Source Artificial Intelligence Tools” and these might be the next tool you use to complete your machine learning project. The article shares that:
Artificial Intelligence (AI) is one of the hottest areas of technology research. Companies like IBM, Google, Microsoft, Facebook and Amazon are investing heavily in their own R&D, as well as buying up startups that have made progress in areas like machine learning, neural networks, natural language and image processing. Given the level of interest, it should come as no surprise that a recent artificial intelligence report from experts at Stanford University concluded that ‘increasingly useful applications of AI, with potentially profound positive impacts on our society and economy are likely to emerge between now and 2030.
The statement reiterates what I already wrote. The list runs down open source tools, including PredictionIO, Oryx 2, OpenNN, MLib, Mahout, H20, Distributed Machine Learning Toolkit, Deeplearning4j, CNTK, Caffe, SystemML, TensorFlow, and Torch. The use of each tool is described and most of them rely on some sort of Apache software. Perhaps your own artificial intelligence project can contribute to further development of these open source tools.
Whitney Grace, October 17, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Google: Fragmentation and the False Universal Search
October 14, 2016
I read “Within Months, Google to Divide Its Index, Giving Mobile Users Better & Fresher Content.” Let’s agree to assume that this write up is spot on. I learned that Google plans “on releasing a separate mobile search index, which will become the primary one.”
The write up states:
The most substantial change will likely be that by having a mobile index, Google can run its ranking algorithm in a different fashion across “pure” mobile content rather than the current system that extracts data from desktop content to determine mobile rankings.
The news was not really news here in Harrod’s Creek. Since 2007, the utility of Google’s search system has been in decline for the type of queries the Beyond Search goslings and I typically run. On rare occasion we need to locate a pizza joint, but the bulk of our queries require old fashioned relevance ranking with results demonstration high precision and on point recall.
Time may be running out for Google Web search.
Several observations:
- With the volume of queries from mobile surpassing desktop queries, why would Google spend money to maintain two indexes? Perhaps Google will have a way to offer advertisers messaging targeted to mobile users and then sell ads for the old school desktop users? If the ad revenue does not justify the second index, well, why would an MBA continue to invest in desktop search? Kill it, right?
- What happens to the lucky Web sites which did not embrace AMP and other Google suggestions? My hunch is that traffic will drop and probably be difficult to regain. Sure, an advertiser can buy ads targeted at desktop users, but Google does not put much wood behind that which becomes a hassle, an annoyance, or a drag on the zippy outfit’s aspirations.
- What will the search engine optimization crowd do? Most of the experts will become instant and overnight experts in mobile search. There will be a windfall of business from Web sites addressed to business customers and others who use mobile but need an old fashioned boat anchor computing device. Then what? Answer: An opportunity to reinvent themselves. Data scientist seems like a natural fit for dispossessed SEO poobahs.
If the report is not accurate, so what? Here’s an idea. Relevance will continue to be eroded as Google tries to deal with the outflow of ad dollars to social outfits pushing grandchildren lovers and the folks who take snaps of everything.
The likelihood of a separate mobile index is high. Remember universal search? I do. Did it arrive? No. If I wanted news, I had to search Google News. Same separate index for scholar, maps, and other Google content. The promise of universal search was PR fluff.
Fragmentation is the name of the game in the world of Alphabet Google. And fragmented services have to earn their keep or get terminated with extreme prejudice. Just like Panoramio (I know. You are asking, “What’s Panoramio?), Google Web search could very well be on the digital glide way to the great beyond.
Stephen E Arnold, October 14, 2016
eBay and Corrigon: Heading in the Right Direction?
October 14, 2016
I find eBay fascinating. Many things for sale; for example, $3,000 Teddy bears. I wonder what those are.
I read “eBay to Acquire Corrigon Ltd.” Interesting. I learned about Corrigon, an Israel-based image search and analysis outfit, about seven years ago. The company’s technology can “look” at a digital image and recognize objects in the image. Coirrigon’s pitch, as I recall it, introduced me to the concept of “dynamic browsing.” I thought most browsing was, by definition, was dynamic, but why ask questions which marketers cannot or will not answer. The buzzwords are the intellectual food which gives me Delhi belly.
One application of Corrigon’s technology is to identify objects in a photo can create a link to a shopping site where one can purchase that object. For instance, I am looking at this image:
The Corrigon system will, in theory, point me to this type of entry on another Web site:
What if I really want the model’s shirt? Well, that may be an issue.
Corrigon has some law enforcement and intelligence applications as well. My hunch is that eBay wants to allow a person to see something, buy something.
The method adds layers and performs image parsing. The method is fine but the approach can add compute cycles. Latency when shopping is a bit of brown bread.
The write up informed me that:
Corrigon’s technology and expertise will contribute to eBay’s efforts with image recognition, classification and image enhancements as part of its structured data initiative. There are three parts to eBay’s structured data initiative: first, collect the data; second, process and enrich the data; and third, create product experiences.Corrigon will support the second and third parts – processing and enriching the data and creating product experiences.
Let’s think about how an eBay user accesses information in the digital flea market now. A person navigates to the site and plugs in keywords. The system then generates a bewildering array of options and some listings. A user then scans and clicks the laundry list of listing. Then the user reads individual listings. Then the user presumably buys the best listing. Heaven help the user who needs to hunt for the link to ask the seller a question. Etc. etc. etc.
eBay’s purchase of Corrigon is going to make eBay into a zippier shopping experience. Well, that’s the theory.
eBay’s challenge is my fave Craigslist and obviously the Bezos beastie. I asked myself, “Perhaps eBay should do some interface work and poke around its core search functionality?”
Stephen E Arnold, October 14, 2016
Definitions of Search to Die For. Maybe With?
October 13, 2016
I read “Search Terminology. Web Search, Enterprise Search, Real Time Search, Semantic Search.” I have included glossaries in some of my books about search. I did not realize that I could pluck out four definitions and present them as a stand alone article. Ah, the wonders of content marketing.
If you want to read the definition with which one can die, either for or with, have at it. May I suggest that you consider these questions prior to your perusing the content marketing write up thing:
Web search
- What’s the method for password protected sites and encrypted sites which exist under current Web technology?
- What Web search systems build their own indexes and which send a query to multiple search systems and aggregate the results? Does the approach matter?
- What is the freshness or staleness of Web indexes? Does it matter that one index may be a few minutes “old” and another index several weeks “old”?
Enterprise search
- How does an enterprise search system deliver internal content points and external content pointers?
- What is the consequence of an enterprise search user who accesses content which is incomplete or stale?
- What does the enterprise search system do with third party content such as consultants’ reports which someone in the organization has purchased? Ignore? Re-license? Index the content and worry later?
- What is the refresh cycle for changed and new content?
- What is the search function for locating database content or rich media residing on the organization’s systems?
Real time search
- What is real time? The indexing of content in the millisecond world of Wall Street? Indexing content when machine resources and network bandwidth permit?
- How does a user determine the latency in the search system because marketers can write “real time” while programmers implement index update options which the search administrator selects?
- What search system indexes videos in real time? YouTube struggles with 10 minute or longer latency with some videos requiring hours before the index points to those videos?
Semantic search
- What is the role of human subject matter experts in semantic search?
- What is the benefit of human-intermediated systems versus person-machine or automated smart indexing?
- How does one address concept drift as a system “learns” from its indexing of information?
- What happens to taxonomies, dictionary lists of entities, and other artifacts of concept indexing?
- What does a system do when encountering documents, audio, and videos in a language different from the language of the majority of a system’s users?
Get the idea that zippy, brief definitions cannot deliver Gatorade to the college football players studying in the dorm the night before a big game?
Stephen E Arnold, October 13, 2016
Funnelback: October Advertising
October 11, 2016
Interesting note. Funnelback, owned by Squiz, is displaying in line, personalized advertising. Today is October 10, 2016. Funnelback’s ad is:
Timely. I think about Valentine’s Day in October. Money well spent?
Stephen E Arnold, October 11, 2016
-
- Subscribe to Beyond Search
Feature archive
News archive
-
