“All mushrooms are edible; but some only once.” ~ Croatian proverb
Google was granted a patent today that could be used to collect a seed set of data about features associated with different types of mushrooms, to “determine whether a specimen is poisonous based on predetermined features of the specimen.” The patent also describes how that process could be used to help filter email spam based upon the features found within the email, or to determine whether images on a page are advertisements, or to determine categories of pages on the Web on the basis of textual features within those pages. The image below, from the patent shows how features about a picture such as height, width, placement on a page, caption, and so on might be examined while determining whether or not it is an advertisement:
This machine-learning approach can be trained with data that produces known outcomes, which could then be applied to very large data sets to classify data according to patterns identified within the seed set of data. When Google published Finding more high quality sites in search in February of 2011, they introduced what would beome known as the Big Panda update. The approach was further elaborated on by Google’s Matt Cutts and Amit Singhal in an Interview at Wired Magazine around a week later in TED 2011: The ‘Panda’ That Hates Farms: A Q&A With Google’s Top Search Engineers.
Continue reading The Google Panda Patent?
As a recent post on Google’s Inside Search blog noted, the Web doesn’t just contain strings of text, but also includes a great amount of information about things. The post was an introduction by Google to search results that would contain a lot more information about things that people might search for, with textual summaries and links to related topics in Google’s sidebar when appropriate. If you create Web pages, perform keyword research, and even search the Web, this presents some new challenges and some new opportunities.
A news story at Fast Company in 2010 carried the interesting title, Bing to Lap Google in Making Search an App? The article tells us about Microsoft finding ways to understand when it might be appropriate to show more than just links to web pages or images or news stories when certain searches might be performed. The “instant answers” displayed in the Bing search results aren’t the informational type results that Google is beginning to display alongside its search results, but are rather more akin to the OneBox type of results that Google has been displaying for a few years.
Bing, Entities, and Knowledge Bases
Continue reading Should You be Doing Concept Research Instead of Keyword Research?
In a Google Inside Search blog post, Introducing the Knowledge Graph: Things, not strings we’re told of a new initiative from Google to show us more information within search results themselves about the things we search for. This is a potentially paradigm shifting view of what a search engine does. The post tells us:
The Knowledge Graph enables you to search for things, people or places that Google knows about—landmarks, celebrities, cities, sports teams, buildings, geographical features, movies, celestial objects, works of art and more—and instantly get information that’s relevant to your query. This is a critical first step towards building the next generation of search, which taps into the collective intelligence of the web and understands the world a bit more like people do.
It’s not a surprise that Google’s been working towards reinventing themselves and what they do. With an increased emphasis on social and real time search results, Google’s been transforming themselves into a way to monitor activities and events in the world as a near real time monitor, rather than just a repository of links to web pages that might satisfy situational and informational needs.
Continue reading All Your Knowledge Bases Belong to Google
There are some changes coming to paid search at Google that sound exciting on the surface, but may leave many guessing how exactly those changes might manifest themselves. Over at the Inside Google Adwords blog, we were greeted with a blog post titled New matching behavior for phrase and exact match keywords on April 17th, that tells us that Google will be returning a few more results for paid advertisements that are phrase and exact match keywords. The post tells us to expect to see this start in mid-May.
While I don’t offer paid search as a service, I do often use the Google Keywords Suggestion Tool, and it left me wondering if the search volumes reported by that tool would change in response to the broader match in Google Adwords. Will it continue to show me only “exact” match volumes for keywords that I enter into the tool, or will it start reporting matches for keywords that are broader? Coincidentally, Google was granted a couple of patents this week involving search advertisements, including one on ways that the search engine might modify or expand the range of terms and phrases that advertisements may be shown for.
The first one that caught my eye was the following, which lists Ramananthan V. Guha as one of the inventors behind the patent. He’s known for a few things, including early work building the first version of RSS, as well as being a major force behind Google Custom Search Engines. He also developed Google’s version of trust rank, as an annotation system from “trusted sources” that could make search results more relevant for certain terms and phrases.
Continue reading SEO Implications of New Matching Approach for Google Ads?
There are many sites that curate content and links on the Web, including many blogs and a number of social sites that do it through submissions by their members, who can also vote upon those submissions. The inventors of PostRank came up with an algorithmic approach to rank articles and blog posts and other content on the Web, and present it to people based upon those rankings. I’ve found a patent application at the USPTO that provides some insights and details on how their approach worked.
Google acquired PostRank last June, as was announced on the PostRank blog on June 3, 2011. Given Google’s increasing move towards looking at more social signals for the potential ranking of content shared by others, it’s worth wondering how this technology might be used by Google, and what the PostRank team might be bringing to the effort. PostRank Co-founder Ilya Grigorik, who now appears to be a web performance analyst with Google, noted in the post announcing the acquisition:
We know that making sense of social engagement data is important for online businesses, which is why we have worked hard to monitor where and when content generates meaningful interactions across the web. Indeed, conversations online are an important signal for advertisers, publishers, developers and consumers—but today’s tools only skim the surface of what we think is possible.
Continue reading PostRank and the Importance of Social Engagement Metrics to SEO
I was looking at the peaks and valleys of traffic in Google Analytics, and thinking of the Google Panda and Penguin updates, and couldn’t stop myself:
Wondering how long it will be before Google runs out of black and white animals to name updates after?
Under a conventional approach to indexing links by a search engine, information about the targeted address that a link is pointed towards might be included in a search engine’s index, as well as the anchor text displayed within the links, and possibly even some text near the link itself. The Google Reasonable Surfer model points to the possibility of other information being collected about a link as well, which could be taken together as a whole to calculate how much value or weight might be passed along by the link to another page under a PageRank link analysis model or even in determining how much weight the anchor text used to point to a link might carry.
The question, Just How Smart are Search Engine Robots has been asked with more frequency lately, and a pending patent application published by Google shows how the search engine might be collecting a whole different type of link behavior information about links that are found on the Web. Given Google’s move towards building their own Chrome Browser and providing access to web pages via alternative screens such as those on smart phones and other handheld devices and television screens, it makes sense for the search engine to capture this kind of information as well. The image from the patent filing below shows sections of links, including target and onclick attributes that the search engine might now be indexing.
Continue reading How Google Might Index Link Behavior Information
A rumor surfaced last week that Google would launch a third party commenting platform to rival Facebook’s. Coincidentally, Google was granted two patents this week describing comment systems, and how comments might be ranked under those systems. But the patents appear to describe comments on two different services from Google that have been discontinued. One of the patents appears to involve Google Sidewiki, which had more of a Web annotation service feel than that of a commenting system, and and the other involves comments on Google Knol.
Google Sidewiki and Google Knol and Commenting
Google Sidewiki enabled people to leave a comment on virtually any page on the Web, and could be accessed through the Google toolbar. A 1999 survey of Web annotation services showed that they have been around since the earliest days of the Web, and they differ from commenting systems in that they’ve been aimed at providing ways for people to leave private or public notes about web pages, sometimes but not necessarily with the participation of the authors of those pages. When Google announced that they were closing down Sidewiki last September, they told us that:
Continue reading Google’s Comment Patents and How Pages’ Web Rankings Might Be Influenced by Commentors’ Reputations