Almost seven years ago, I started thinking about what documents I would recommend that people read if they wanted to learn as much about SEO as possible. SEO by the Sea was a little more than a couple of months old, and I started a series of posts that I called the “100 best SEO documents of all time.” I started the series knowing the first 30 papers, blog posts, and patents that I wanted to include in the series, and somehow never got past those first thirty.
The posts were the three posts immediately before the gathering that originally gave SEO by the Sea its name. I went from blogger to event organizer, and never quite returned back to the series that I started. In the past couple of days, the first post got some attention on Twitter, and I promised to update the series.
The next ten documents are ones that I’ve been thinking about quite a bit after reading them, and what they might mean for the future of search.
Search engines are hard at work transforming the Web from a place of words to a place of people, places, and things. An Ars Technica article from earlier this month, How Google and Microsoft taught search to “understand” the Web, discusses this evolution of the web, though I think they see this trend incorrectly as one that only goes back a few years.
The first post I wrote about search engines extracting entities from webpages was in January of 2006, in Providing related links to documents. I’ve written a number more that describe how the identification and extraction of an entity from a page might be useful in one manner or another to a search engine. This is true with local search, as well as with practices that can drastically impact the composition of the search results that we see everyday. Over at the SEOmoz blog a couple of days ago, Dr. Pete Myers wrote The Bigfoot Update (AKA Dr. Pete Goes Crazy).
Google employs human evaluators to judge the relevance of web pages in search results, but according to Google’s Matt Cutts, usually only when engineers from the search engine are testing a new algorithm, and want to compare the results with the ranking algorithms that they might be replacing. (We’ve also seen that Google likely uses human evaluators to uncover web spam as well.) Matt Cutts answered a question on how Google uses human evaluators in a video filmed last month:
Google was granted a patent today originally filed in July of 2005, that describes how human evaluators might be used to test algorithms, as well as in actual live ranking systems for local search and for web search. Those evaluations of search results pages for specific queries could be used in a statistical model that might influence search results. Google may only be using human evaluators for purposes of testing search results (and finding web spam), but it’s interesting to see both the testing and ranking approaches described within a patent from Google.
Google Glasses have the potential to make a growing number of types of visual queries that are possible under Google Goggles into an important aspect of the future of search and SEO. They also may make advertising using location based services much more effective. Are you planning ahead?
Over the last three weeks, we’ve been seeing a stream of patents granted to Google involving their heads up display device, Project Glass. These include design patents, and utility patents that hint at things like a touchscreen on the side of the glasses, sonar sensors built into them, a visual display of sounds around the wearer of the glasses including direction and intensity. I wrote about the first two batches of patents in Google Glasses Design Patents and Other Wearables and More Google Glasses Patents: Beyond the Design. Google was granted another related patent this past week titled Methods and devices for augmenting a field of view this week, which “augments” the field of view of human beings by helping things that might be of interest stand out, even if they are beyond the normal view of a person in terms of distance or outside of a 180 degree peripheral viewing field.
“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:
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.
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.
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.