Monthly Archives: October 2018
How A Knowledge Graph Updates Itself
To those of us who are used to doing Search Engine Optimization, we’ve been looking at URLs filled with content, and links between that content, and how algorithms such as PageRank (based upon links pointed between pages) and information retrieval scores based upon the relevance of that content have been determining how well pages rank in search results in response to queries entered into search boxes by searchers. Web pages connected by links have been seen as information points connected by nodes. This was the first generation of SEO.
Search has been going through a transformation. Back in 2012, Google introduced something it refers to as the knowledge graph, in which they told us that they would begin focusing upon indexing things instead of strings. By “strings,” they were referring to words that appear in queries, and in documents on the Web. By “things,” they were referring to named entities, or real and specific people, places, and things. When people searched at Google, the search engines would show Search Engine Results Pages (SERPs) filled with URLs to pages that contained the strings of letters that we were searching for. Google still does that, and is slowly changing to showing search results that are about people, places, and things.
Google started showing us in patents how they were introducing entity recognition to search, as I described in this post:
How Google May Perform Entity Recognition
They now show us knowledge panels in search results that tell us about the people, places, and things they recognize in the queries we perform. In addition to crawling webpages and indexing the words on those pages, Google is collecting facts about the people, places, and things it finds on those pages.
A Google Patent that was just granted in the past week tells us about how Google’s knowledge graph updates itself when it collects information about entities, their properties and attributes and relationships involving them. This is part of the evolution of SEO that is taking place today – learning how Search is changing from being based upon search to being based upon knowledge.
What does the patent tell us about knowledge? This is one of the sections that details what a knowledge graph is like that Google might collect information about when it indexes pages these days:
Knowledge graph portion includes information related to the entity [George Washington], represented by [George Washington] node. [George Washington] node is connected to [U.S. President] entity type node by [Is A] edge with the semantic content [Is A], such that the 3-tuple defined by nodes and the edge contains the information “George Washington is a U.S. President.” Similarly, “Thomas Jefferson Is A U.S. President” is represented by the tuple of [Thomas Jefferson] node 310, [Is A] edge, and [U.S. President] node. Knowledge graph portion includes entity type nodes [Person], and [U.S. President] node. The person type is defined in part by the connections from [Person] node. For example, the type [Person] is defined as having the property [Date Of Birth] by node and edge, and is defined as having the property [Gender] by node 334 and edge 336. These relationships define in part a schema associated with the entity type [Person].
Note that SEO is no longer just about how often certain words appear on pages of the Web, what words appear in links to those pages, in page titles, and headings, alt text for images, and how often certain words may be repeated or related words may be used. Google is looking at the facts that are mentioned about entities, such as entity types like a “person,” and properties, such as “Date of Birth,” or “Gender.”
Note that quote also mentions the word “Schema” as in “These relationships define in part a schema associated with the entity type [Person].” As part of the transformation of SEO from Strings to Things, The major Search Engines joined forces to offer us information on how to use Schema for structured data on the Web to provide a machine readable way of sharing information with search engines about the entities that we write about, their properties, and relationships.
I’m writing about this patent because I am participating in a Webinar online about Knowledge Graphs and how those are being used, and updated. The Webinar is tomorrow at:
#SEOisAEO: How Google Uses The Knowledge Graph in its AE algorithm. I haven’t been referring to SEO as Answer Engine Optimization, or AEO and it’s unlikely that I will start, but see it as an evolution of SEO
I’m writing about this Google Patent, because it starts out with the following line which it titles “Background:”
This disclosure generally relates to updating information in a database. Data has previously been updated by, for example, user input.
This line points to the fact that this approach no longer needs to be updated by users, but instead involves how Google knowledge graphs update themselves.
Updating Knowledge Graphs
I attended a Semantic Technology and Business conference a couple of year ago, where the head of Yahoo’s knowledge base presented, and he was asked a number of questions in a question and answer session after he spoke. Someone asked him what happens when information from a knowledge graph changes and it needs to be updated?
His Answer was that a knowledge graph would have to be updated manually to have new information place within it.
That wasn’t a satisfactory answer because it would have been good to hear that the information from such a source could be easily updated. I’ve been waiting for Google to answer a question like this, which made seeing a line like this one from this patent a good experience:
In some implementations, a system identifies information that is missing from a collection of data. The system generates a question to provide to a question answering service based on the missing information, and uses the response from the question answering service to update the collection of data.
This would be a knowledge graph update, so that patent provides details using language that reflects that exacly:
In some implementations, a computer-implemented method is provided. The method includes identifying an entity reference in a knowledge graph, wherein the entity reference corresponds to an entity type. The method further includes identifying a missing data element associated with the entity reference. The method further includes generating a query based at least in part on the missing data element and the type of the entity reference. The method further includes providing the query to a query processing engine. The method further includes receiving information from the query processing engine in response to the query. The method further includes updating the knowledge graph based at least in part on the received information.
How does the search engine do this? The patent provides more information that fills in such details.
The approaches to achieve this would be to:
…Identifying a missing data element comprises comparing properties associated with the entity reference to a schema table associated with the entity type.
…Generating the query comprises generating a natural language query. This can involve selecting, from the knowledge graph, disambiguation query terms associated with the entity reference, wherein the terms comprise property values associated with the entity reference, or updating the knowledge graph by updating the data graph to include information in place of the missing data element.
…Identifying an element in a knowledge graph to be updated based at least in part on a query record. Operations further include generating a query based at least in part on the identified element. Operations further include providing the query to a query processing engine. Operations further include receiving information from the query processing engine in response to the query. Operations further include updating the knowledge graph based at least in part on the received information.
A knowledge graph updates itself in these ways:
(1) The knowledge Graph may be updated with one or more previously performed searches.
(2) The knowledge Graph may be updated with a natural language query, using disambiguation query terms associated with the entity reference, wherein the terms comprise property values associated with the entity reference.
(3) The knowledge Graph may use properties associated with the entity reference to include information updating missing data elements.
The patent that describes how Google’s knowledge graph updates themselves is:
Question answering to populate knowledge base
Inventors: Rahul Gupta, Shaohua Sun, John Blitzer, Dekang Lin, Evgeniy Gabrilovich
US Patent: 10,108,700
Granted: October 23, 2018
Filed: March 15, 2013
Methods and systems are provided for a question answering. In some implementations, a data element to be updated is identified in a knowledge graph and a query is generated based at least in part on the data element. The query is provided to a query processing engine. Information is received from the query processing engine in response to the query. The knowledge graph is updated based at least in part on the received information.
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Over the past two years, the notch moved from anomaly to fact of life, and no company has proven itself more pro-notch than Google. From its embrace of #notchlife in Android Pie to the downright gigantic one found up top on the Pixel 3 XL, Google’s really notchin’ it up.
In fact, as noted by Android Police, the Pixel 3 XL has a notch so nice, Google’s delivering it twice. A number of owners have reported an admittedly hilarious bug that’s causing the massive handset to double up on the notch, with a second cutout appearing on the side of the device.
— UrAvgConsumer (@UrAvgConsumer) October 24, 2018
Google has acknowledged (acknotchleged?) the issue and noted that it’s working on a fix, which should be coming soon. The company hasn’t offered a reason behind the issue, but it appears to stem from Pie’s built-in notch feature, and likely has something to do with how the background adjusts when the handset changes from portrait to landscape mode.
It seems even in 2018, that’s a notch too far.
Cockroach Lab’s open source SQL database, CockroachDB, has been making inroads since it launched last year, but as any open source technology matures, in order to move deeper into markets it has to move beyond technical early adopters to a more generalized audience. To help achieve that, the company announced a new CockroachDB managed service today.
The service has been designed to be cloud-agnostic, and for starters it’s going to be available on Amazon Web Services and Google Cloud Platform. Cockroach, which launched in 2015, has always positioned itself as modern cloud alternative to the likes of Oracle or even Amazon’s Aurora database.
As company co-founder and CEO Spencer Kimball told me in an interview in May, those companies involve too much vendor lock-in for his taste. His company launched as open alternative to all of that. “You can migrate a Cockroach cluster from one cloud to another with no down time,” Kimball told TechCrunch in May.
He believes having that kind of flexibility is a huge advantage over what other vendors are offering, and today’s announcement carries that a step further. Instead of doing all the heavy lifting of setting up and managing a database and the related infrastructure, Cockroach is now offering CockroachDB as a service to handle all of that for you.
Kimball certainly recognizes that by offering his company’s product in this format, it will help grow his market. “We’ve been seeing significant migration activity away from Oracle, AWS Aurora, and Cassandra, and we’re now able to get our customers to market faster with Managed CockroachDB,” Kimball said in a statement.
The database itself offers the advantage of being ultra-resilient, meaning it stays up and running under most circumstances and that’s a huge value proposition for any database product. It achieves up time through replication, so if one version of itself goes down, the next can take over.
As an open source tool, it has been making money up until now by offering an enterprise version, which includes backup, support and other premium pieces. With today’s announcement, the company can get a more direct revenue stream from customers subscribing to the database service.
A year ago, the company announced version 1.0 of CockroachDB and $ 27 million in Series B financing, which was led by Redpoint with participation from Benchmark, GV, Index Ventures and FirstMark. They’ve obviously been putting that money to good use developing this new managed service.
Snapchat continued to shrink in Q3 2018 but its business is steadily improving. Snapchat’s daily active user count dropped again, this time by 1 percent to 186 million, down from 188M and a negative 1.5 percent growth rate in Q2. User count is still up 5 percent year-over-year, though. Snapchat earned $ 298 million in revenue with an EPS loss of $ 0.12, beating Wall Street’s expectations of $ 283 million in revenue and EPS loss of $ 0.14, plus a loss of a half a million users.
Snap entered earnings with a $ 6.99 share price, close to its $ 6.46 all-time low and way down from its $ 24 IPO opening price. Snap lost $ 325 million this quarter compared to $ 353 million in Q2, so it’s making some progress with its cost cutting. That briefly emboldened Wall Street, which pushed the share price up 8.3 percent to around $ 7.57 right after earnings were announced.
But then Snap’s share price came crashing down to -9.3 percent to $ 6.31 in after-hours trading. The stock had been so heavily shorted by investors that it only needed modest growth in its business for shares to perk up, but the fear that Snap might shrink into nothing has investors weary. Projections that Snap will lose users again next quarter further scared off investors.
Worringly, Snapchat’s average revenue per user dropped 12.5 percent in the developing world this quarter. But strong gains in the US and Europe markets grew global ARPU by 14 percent. Snap projects $ 355 million to $ 380 million in holiday Q4 revenue, in line with analyst estimates.
In his prepared remarks, CEO Evan Spiegel admitted that “While we have incredible reach among our core demographic of 13- to 34-year-olds in the US and Europe, there are billions of people worldwide who do not yet use Snapchat.” He explained that the 2 million user loss was mostly on Android where Snapchat doesn’t run as well as on iOS. Noticibly absent was an update on monthly active users in the US and Canada. Snap said that was over 100 million monthly users last quarter, probably in an effort to distract from the daily user shrinkage. The company didn’t update that stat, but did say the “over 100 million” stat was still accurate.
Spiegel had said in a memo that his stretch goal was break-even this year and full-year profitability in 2019. But CFO Tim Stone said that “Looking forward to 2019, our internal stretch output goal will be an acceleration of revenue growth and full year free cash flow and profitability. Bear in mind that an internal stretch goal is not a forecast, and it’s not guidance.”
During the call, Spiegel responded to questions about the Android overhaul’s schedule saying, “Quality takes time. We’re going wait until we get it right”. But analysts piled on with inquiries about how Snap would turn things around in 2019. He admitted Snaps created per day had dropped from 3.5 billion to 3 billion per day, but tried to reassure investors by saying over 60% of our users are still creating snaps every day.
Spiegel said that expanding beyond the 13 to 34-year-old age group in the US and Europe, plus scoring more users in the developing world via the improved Android app would be how it restores momentum. But the problem is that courting older users could sour the perception of its younger users who don’t want their parents, teachers, or bosses on the app.
Now down to $ 1.4 billion in cash and securities, Snap will need to start reaching more of those international users or improving monetization of those it still has to keep afloat without outside capital.
An Uphill Battle
Q3 saw Snapchat’s launch its first in-house augmented reality Snappable games, while plans for an third-party gaming platform leak. The Snappable Tic-Tac-Toe game saw 80 million unique users, suggesting gaming could be the right direction for Snap to move towards.
It launched Lens Explorer to draw more attention to developer and creator-built augmented reality experiences, plus its Storyteller program to connect social media stars to brands to earn sponsorship money. It also shut down its Venmo-like Snapcash feature. But the biggest news came from its Q2 earnings report where it announced it’d lost 3 million users. That scored it a short-lived stock price pop, but competition and user shrinkage has pushed Snap’s shares to new lows.
Snapchat is depending on the Project Mushroom engineering overhaul of its Android app to speed up performance, and thereby accelerate user growth and retention. Snap neglected the developing world’s Android market for years as it focused on iPhone-toting US teens. Given Snapchat is all about quick videos, slow load times made it nearly unusable, especially in markets with slower network connections and older phones.
Looking at the competitive landscape, WhatsApp’s Snapchat Stories clone Status has grown to 450 million daily users while Instagram Stories has reached 400 million dailies — much of that coming in the developing world, thereby blocking Snap’s growth abroad as I predicted when Insta Stories launched.. Snap Map hasn’t become ubiquitous, Snap’s Original Shows still aren’t premium enough to drag in tons of new users, Discover is a clickbait-overloaded mess, and Instagram has already copied the best parts of its ephemeral messaging. Snap could be vulnerable in the developing world if WhatsApp similarly copies its disappearing chats.
At this rate, Snap will run out of money before it’s projected to become profitable in 2020 or 2021. That means the company will likely need to sell new shares in exchange for outside investment or get acquired to survive.
To keep up with the rising demand for short-term rentals in U.S. cities and compete with the home-sharing giant Airbnb, travel booking site Expedia has picked up a pair of venture-backed hospitality startups, Pillow and ApartmentJet.
Employees of both companies will join Expedia . The company declined to disclose the financial terms of the deals.
“Acquiring Pillow and ApartmentJet will help unlock urban growth opportunities that, over time, will contribute to HomeAway’s ability to add an even broader selection of accommodations to its marketplace and marketplaces across Expedia Group brands, ensuring travelers always find the perfect place to stay,” the company explained in a statement.
Expedia paid $ 3.9 billion for HomeAway and its portfolio of travel brands in 2015. The deal was its first major move in the alternative accommodations space, as well as the beginning of a series of efforts to outdo VC darling Airbnb. Its latest targets provide software tools for property managers to easily manage short-term rentals on Airbnb competitors like HomeAway and VRBO.
Located in San Francisco, Pillow helps residents list their apartments as short-term rentals without violating their leases. It’s raised a total of $ 16.5 million in VC backing since 2013, including a $ 13.5 million round last year led by Mayfield, with participation from Sterling.VC, Peak Capital Partners, Expansion VC, Chris Anderson, Gary Vaynerchuk, Dennis Phelps and Veritas Investments.
ApartmentJet helps property owners earn money off vacancies. Founded in 2016, the Chicago-headquartered startup had raised a reported $ 1.2 million in capital from Network Ventures and BlueTree.
Bellevue-based Expedia Group owns several travel brands, including HomeAway, VRBO, Travelocity, trivago, Orbitz and Hotels.com. The company is both an active investor in and acquirer of startups.
Expedia’s shares rose 9.4 percent Thursday after its third-quarter earnings beat analyst expectations. The company posted $ 3.28 billion in revenue, a notable increase from last year’s $ 2.97 billion.
The Pentagon’s $ 10 billion JEDI cloud contract bidding process has drawn a lot of attention. Earlier this month, Google withdrew, claiming ethical considerations. Amazon’s Jeff Bezos responded in an interview at Wired25 that he thinks that it’s a mistake for big tech companies to turn their back on the U.S. military. Microsoft president Brad Smith agrees.
In a blog post today, he made clear that Microsoft intends to be a bidder in government/military contracts, even if some Microsoft employees have a problem with it. While acknowledging the ethical considerations of today’s most advanced technologies like artificial intelligence, and the ways they could be abused, he explicitly stated that Microsoft will continue to work with the government and the military.
“First, we believe in the strong defense of the United States and we want the people who defend it to have access to the nation’s best technology, including from Microsoft,” Smith wrote in the blog post.
To that end, the company wants to win that JEDI cloud contract, something it has acknowledged from the start, even while criticizing the winner-take-all nature of the deal. In the blog post, Smith cited the JEDI contract as an example of the company’s desire to work closely with the U.S. government.
“Recently Microsoft bid on an important defense project. It’s the DOD’s Joint Enterprise Defense Infrastructure cloud project – or “JEDI” – which will re-engineer the Defense Department’s end-to-end IT infrastructure, from the Pentagon to field-level support of the country’s servicemen and women. The contract has not been awarded but it’s an example of the kind of work we are committed to doing,” he wrote.
He went on, much like Bezos, to wrap his company’s philosophy in patriotic rhetoric, rather than about winning lucrative contracts. “We want the people of this country and especially the people who serve this country to know that we at Microsoft have their backs. They will have access to the best technology that we create,” Smith wrote.
Throughout the piece, Smith continued to walk a fine line between patriotic duty to support the U.S. military, while carefully conceding that there will be different opinions in a large and diverse company population (some of whom aren’t U.S. citizens). Ultimately, he believes that it’s critical that tech companies be included in the conversation when the government uses advanced technologies.
“But we can’t expect these new developments to be addressed wisely if the people in the tech sector who know the most about technology withdraw from the conversation,” Smith wrote.
Like Bezos, he made it clear that the company leadership is going to continue to pursue contracts like JEDI, whether it’s out of a sense of duty or economic practicality or a little of both — whether employees agree or not.
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