On Friday afternoon, I took a walk to the auto repair shop working on my car, about a mile and a half down the road. A phone alert made me aware of a Google Now card springing up to give me directions to the shop, and telling me that it would take me less than a minute to get there. I guess Google Now wasn’t looking at the accelerometer on my phone, or it would have realized that I was moving too slowly to be driving. I couldn’t help but think though how Google Now could be a feature that would work well in the heads up display that Google’s working on under the name Google Glass.
As we wait to see what kinds of features might be incorporated into Google Glass, it appears that Google acquired a patent first filed a dozen years ago, granted in 2006, and recorded at the USPTO on Thursday. The patent was originally filed by Agilent Technologies, transferred to a company in Singapore in 2006, and then to Intellectual Discovery Co., located in South Korean. Google was assigned the patent on November 16, 2012, and the transaction was recorded at the USTPO on January 8, 2013.
When we talk about indexing and crawling content on the Web, it’s usually within the context of pages being ranked on the basis of a number of signals found on Web pages that might be ranked in response to queries. Google has told us that the future of search involves Knowledge Bases, and the indexing of Things, Not Strings. Gianluca Fiorelli explored Google’s ideas of Search in the Knowledge Graph Era earlier this week.
A few years back, I wrote some posts about some Google Patents that explored how Google might be extracting and visualizing facts, and using Data Janitors to process that information and clean it up and sort it. Google was granted another patent this week that’s very much related, looking at how Google might understand locations for places collected from Web pages. One of the inventors, Andrew Hogue, gave this Google Tech Talk presentation last year:
When someone searches at Google, their query might not express the informational or situational need that they have. It might be too broad, too ambiguous, or vague in some other manner. A well-formulated query instead might contain terms returing resources addressing the searcher’s intent, which might be measured by performance metrics. For vague queries, search results that satisfy a searcher’s need for information might not be highly ranked, and may not be presented on a first page of search results.
Well Performing Queries as Search Suggestions
A search engine may identify well-performing queries from queries entered by users. This is especially true in cases where many searchers have selected results from those queries. These well-performing queries may be suggested to searchers when similar queries are presented to a search engine.
The most important step in doing keyword research is entering a keyword phrase into a search engine like Google, and seeing what results show up, and trying to understand why the pages that appear within results are there. If you can’t do that, then it’s time to dig down and start learning.
Whether you’re a searcher looking for information on the Web, or someone doing keyword research for a website, it’s important to have an idea of the many different ways that a search engine might treat a search you perform. For instance, if your search is one that might trigger Google to show results from a specific web page associated with a named entity (a particular person, place, or thing) at the top of those results, you shouldn’t necessarily be surprised to see that site listed first in search results. This is something that is done algorithmically by Google. Just stating that Google has a “magical” brand preference is a mistake in that instance. It’s better to try to understand how that algorithm might be triggered instead.
Likewise, when you perform a search for a term such as [hospice], Google might decide to show a map result from Google Maps in Web search results because their universal search algorithm suggests that the query has a local intent, and the searcher is likely looking for a nearby hospice. Again, it would be a mistake to make the assumption that Google is favoring their own “property” in Google Maps when the reality is that the vertical search result of Google Maps is what searchers are actually looking for.
Imagine the Earth broken down into a series of cells, and each of those cells broken down into a series of even smaller cells, and then into smaller cells again, and so on, in a spatial index. Each of the levels become increasingly narrow, and increasingly more precise areas or zoom levels of the surface of the Earth.
As these cells decrease in size, they increase in numbers, which has the impact of increasing the zoom level and the accuracy of areas represented in such an index. Might work good in a place like China, where latitude and longitude are banned for export as munitions. Such a set of cells might be part of a geospatial analyzing module that links specific businesses and points of interest (parks, public regions, landmarks, etc.) to specific places on this model or index of the earth. That might be one index of the businesses and one index for the points of interest, or a combined database that includes both.
Sometimes that index might include a business and a landmark within the same cell. While that could be correct in some instances, such as a shop appearing within the Empire State Building, Often its an error, and sometimes even an intentional error. People will sometimes enter incorrect information into a geographic system like this to try to gain some kind of advantage.
If people search for something like a motel “near” a particular park for instance, the motel that appears to be next to, or even within the boundaries of that part might seem to have something of an an advantage in terms of distance from that part when it comes to ranking the motel. And, sometimes Google doesn’t seem to do the best job in the world at putting businesses in the right locations at Google Maps.
When Google ranks businesses at locations in Google Maps, they turn to a number of sources to find mentions of the name of the business coupled with some location data. They can look at the information that a site owner might have provided when verifying their business with Google and Bing and Yahoo. They may look at sources that include business location information such as telecom directories like superpages.com or yellowpages.com. or business location databases such as Localeze. They likely also look at the website for the business itself, as well as other websites that might include the name of the business and some location data for the business, too.
What happens when the information from those sources doesn’t match. Even worse, what happens when one of these sources includes information that might be on the spammy side? A patent granted to Google this week describes a way that Google might use to police for such places. The patent warns against titles for business entities that include terms such as “cheap hotels,” “discounts,” Dr. ABC–555 777 8888.” It also might identify spam in categories for businesses that might include things such as “City X,” “sale,” “City A B C D,” “Hotel X in City Y,” and “Luxury Hotel in City Y.”
In the context of a business entity, information that skews the identity of or does not accurately represent the business entity or both is considered spam.
I sometimes see people say that paid search is a great way to do keyword research for SEO, but I disagree with that statement. Paid search primarily focuses upon keywords that are transactional in nature – usually the terms chosen are the kind that match an intent to buy something, download something, or take some other kind of action. I’ve asked many people who do search engine advertising, and focus on Adwords if they ever target queries that are informational in nature, and most of the time the answer has been no.
Often searchers will do some research on a product or service before they decide who to buy from. They will perform research to find what kinds of features are available for different products, try to find reviews or opinions from others, They may try to compare different manufacturers as well. These types of queries are more informational in nature, and the same searcher will conduct these types queries that evidence an informational intent before they begin to consider a query with a transactional intent.
Rand noted that first page rankings for three different pages, which didn’t seem very much optimized for the queries they were returned for, might be ranked based upon a ranking signal that looks at how words tend to co-occur on pages related to those queries. My post in response explored some reranking approaches by Google that also might account for those rankings, including Phrase Based Indexing, Google’s Reasonable Surfer Model, Named Entity Associations, Category associations involving categories assigned to queries and categories assigned to webpages, and Google’s use of synonyms in place of terms within queries.
Google’s Phrase-Based Indexing approach pays a lot of attention to words (phrases, actually) that appear together, or co-occur, in the top (10/100/1,000) search results for a query and may boost pages in rankings based upon that co-occurrence, and seemed like a possible reason why those pages might be appearing on the first page of results. The other reranking approaches that I included also seemed like they might be in part or in full responsible for the rankings as well. Then I found a patent granted to Google this week that seems like an even better fit.