Tomorrow morning, I’m presenting on the Semantic Web at Google at Pubcon in Las Vegas. I’ve included my presentation deck here to use as a kicking off point for further discussion.
Changes to what Google shows in search results have been difficult to miss, from many different types of rich snippets to recent additions of search boxes in search results and Google showing snippets from pages that contain both query answering and question answering results mixed together.
Thanks to Barbara Starr for taking a look at the presentation, and for suggesting that I look for a Google patent for rich snippets which I hadn’t included. I went searching the patent in the US Patent office and found a good candidate for it, and will probably post a more detailed look at that one in the near future. It’s Generating specialized search results in response to patterned queries.
Here’s my presentation:
Continue reading At Pubcon, Presenting on a Semantic Timeline at Google
It was a surprise to see a number of Yahoo! patents listed in Google’s assignment database as having been assigned to Google. With news recently that Yahoo would be closing the Yahoo Directory, that seemed like a strategic choice. Now I’m wondering if we will ever see an independent Yahoo Search Engine ever again once their deal to have Microsoft supply search results to them ends.
The USPTO assignment database doesn’t disclose financial details of transactions like this, so we don’t know things like how much the transaction cost or if there were licensing agreements accompanying the transaction.
A number of these patents seem to have orginated at Yahoo!, but some were acquired by Yahoo when they acquired companies such as Altavista and Inktomi. Fastforward Technologies specialized in multi streaming broadcast technologies and was originally acquired by Inktomi.
Continue reading Google Acquires 55 Yahoo! Patent Filings
The Semantic Web is making an even stronger appearance recently at Google than it has in the past. With knowledge panels, carousels listing all kinds of things (and people and places), structured snippets merging query answers with question answers into a single snippet, OneBoxes of many different kinds, and even Hummingbird responding better to longer and more complex queries, it’s the future of Google.
I’m presenting on it this morning at the Javit’s Center in Manhattan at SMX (Search Marketing Expo) East, in a session titled “Hummingbird and the Entity Revolution”
Continue reading At SMX East; Presenting on Google and the Semantic Web
Google’s Pierre Far announced on his Google+ page that Google was releasing a new Panda update that supposedly included some new signals that could potentially help “identify low-quality content more precisely.”
The Google+ post also tells us that this change can help lead to a “greater diversity of high-quality small- and medium-sized sites ranking higher, which is nice.”
A new patent application shows off a quality scoring approach for content, based upon phrases. More on that patent filing below, but it might have something to do with this update.
Continue reading New Panda Update; New Panda Patent Application
It can be difficult classifying a query for a search engine based upon the query itself.
For example, you could classify the query “lincoln” based upon:
President Abraham Lincoln
The location, Lincoln,Nebraska
Continue reading Using Query User Data to Classify Queries
In the past few years, Google has been busy building what has become known as the Google Brain team, which started out by having its deep learning approach watching videos until it learned to recognize cats.
Google has been hiring a number of people to add to the abilities of their deep learning team, including a pricy acqui-hire in the UK earlier this year, as described in More on DeepMind: AI Startup to Work Directly With Google’s Search Team
Web Spam Classification Patent
Continue reading Google Turns to Deep Learning Classification to Fight Web Spam
In creating a knowledge base, there seem to be a number of approaches that can be used to supply entities and facts from sources like web pages and query logs.
In my last post, I wrote about how search queries might be used, along with linguistic patterns, to extract attributes about facts from those search queries, as described in a patent titled Inferring attributes from search queries.
A Microsoft paper from 2009, Named Entity Recognition in Query, tells of a manual analysis they performed of 1,000 queries, and told us that 70% of those queries contained named entities.
So entities do appear in queries, and Google receives a lot of queries a day (as does Microsoft and Yahoo).
Continue reading Extracting Semantic Classes and Corresponding Instances from Web Pages and Query Logs
Millions of searches stream into Google everyday as people try to meet their informational and situational needs. But those searches don’t disappear after the searches. They provide Google with some very interesting and useful information in return. For instance, they tell Google what people are interested in real time – right at this moment.
Those queries can help Google populate its knowledge base with more information as well.
When Google collects information about entities – people, places, and things, including products and brands, it might collect information about entities as well as information about attributes associated with those entities.
A couple of days ago, the Google Research Blog told us about how it might include that kind of factual information in search results, what they called Structured Snippets. In that post, Google gave us the news that Google finds information like this from Tables across the web.
Continue reading How Google May Add to its Knowledge Base with Entities and Attributes from Search Queries