The internet is a vast expanse with many different neighborhoods. Each has its unique features – streets lined with shops or restaurants, parks ripe for an afternoon stroll, museums stocked full of interesting exhibitions. A person can spend hours exploring these various parts of town without ever venturing too far away from home base!
People don’t want to know where businesses are across the country (unless they plan a trip), but they want to know what is immediately close to them to fulfill that search intent. This is why local SEO is a vital aspect of your digital strategy.
How do Search Engines Gather information on Local Searches?
As people perform Geographical and Local search queries, these searches build the search engine’s index to give more information about relevant search results to the user for that area. The false positives get weeded out, and the correct results build a list of qualified results.
Microsoft’s Locations Search Query Patent
Detecting Dominant Locations from Search Queries, a paper written by Microsoft Research examines the “location intent” of the search. It attempts to understand a “dominant location” of a query based upon many resulting answers.
The processes described in the US Patent and Trademark Office:
Search query dominant location detection Patent
Invented by Chuang Wang, Joshua Forman, Lee Wang, Xing Xie, Ying Li
Assigned to Microsoft
US Patent Application 20060271518
Published November 30, 2006
Filed: May 27, 2005
A system and method for location-specific searching. The invention correctly identifies explicit and implicit locations in a search query and provides an appropriate dominant location. Top search results are obtained and analyzed to determine which terms in the query often appear in combination, and the query is tokenized based on the analysis. An explicit location indicating a location intent is most likely treated as an individual token, and the explicit location is treated as the dominant location of the query. In the case of a false positive, wherein the explicit location in a query is not the location intent, the explicit location is likely to be present with other terms that provide context. A token will likely include these terms together. The explicit location will therefore not be used to generate location-specific results in the case of a false positive.
Explicit & Implicit Locations in Queries
The patent defines explicit and implicit location factors in search results:
Location intent is an implication in a search that the searcher seeks something related to a geographic area.
An example of this would be searching for “Ottawa restaurant,” from that query, the search engine understands you are looking for restaurants in Ottawa.
Searching for “Outback Steakhouse” isn’t necessarily looking for steakhouses in the Australian Outback, but a chain restaurant. In some cases, it can cause false negatives and false positives. Search engines should be able to figure this out using their topical knowledge base.
A search result can show precise locations and implicit locations in one query. This precise and implicit result could be a subway sandwich shop at a subway station entrance in New York City.
Explicit location – a geographical name that is present in the query. So, the term “Ottawa” in the query “Ottawa Restaurant” is seen as an explicit location. But, we’ve also seen from the Outback Steakhouse example that an exact location in a search may not be the actual location intent of the searcher.
The patent application uses a different example of a query that uses a geographical location that doesn’t represent a location intent:
“Indiana” is the explicit location of the query “Indiana Jones,” but it is not the location intent.
Implicit location – You can also have location searches that do not have the city’s name but can still be used with Location Intent.
An example of this is “restaurant near CN Tower,” which is an implicit search because it references a landmark rather than a geographical location. The implication is that the searcher is looking for a restaurant in downtown Toronto.
IP-Based Results vs. Dominant Location Results
Another technique that could provide searchers with location-specific results relies upon a reverse IP lookup of the user’s physical location.
IP-based results are not helpful when someone is researching information on distant locations.
The patent application instead looks to a “dominant location” for a query:
A dominant location is, for example, a prominent location that is agreed upon by a majority of people who know the answer to the query.
If a query has a dominant location, it may be used as the location intent for that query.
However, detecting a dominant location is difficult because it is a subjective and collective measure: it is the location existing in the collective human knowledge.
How website locations affect search
On the flip side, to complete search intent analysis, you will also need to understand where the websites are located to match a relevant search.
Similar to a Map, you need a starting point and a destination point. The searcher would be the starting point, whereas the destination is the local website.
Types of Locations
A paper from Microsoft Research: Web Resource Geographic Location Classification and Detection (pdf) discuss three different types of locations for websites:
Provider-Location – The actual geographic location of the owner of a website.
Content-Location – The location that the content of a site may be about.
Serving-Location – The geographic scope of the audience that the site aims to reach.
Classification & Detection algorithms show us it is vital to have an address (NAP) on every page of your website, relevant content to your location, and clearly distinguish where you perform business. It might be evident to people where your business is located, but search crawlers might need more help.
Method and system for web resource location classification and detection
Invented by Chuang Wang, Wei-Ying Ma, and Xing Xie
Assigned to Microsoft
US Patent Application 20060206624
Published September 14, 2006
Filed: March 10, 2005
A method and system for identifying locations associated with a web resource is provided. The location system identifies three different types of geographic locations: a provider location, a content location, and a serving location. A provider location identifies the geographic location of the entity that provides the web resource. A content location identifies the geographic location that is the subject of the web resource. A serving location identifies the geographic scope that the web page reaches. An application can select to use the type of location that is of particular interest.
Why is this type of information necessary to search engines?
People want relevant information about the surrounding areas they live in. If they need gas, food, or help, they typically require immediate and local results. If search engines cannot accomplish this, they will use another service to find this information.
Credit must be given to Bill Slawski; I started reading his articles and found them too advanced, so I started re-writing them to understand the patents better. For a more advanced understanding of these patents, please check out his blog.
How does Location Queries affect Search Results?
The notion of location is central to the way in which we understand and interact with the world. When we search for something on the internet, we are often looking for information that is specific to a particular place. For example, if we want to find a restaurant in our town, we might enter the query “restaurants in [town name].” This type of query is known as a location query. Location queries can have a significant impact on search results. This is because different places often have different concentrations of businesses and organizations that offer the same or similar products and services. As a result, a location query can help to narrow down the field of potential search results and make it easier to find the information that we are looking for. In addition, location queries can also be used to personalize search results. For example, if we live in New York but enter the query “restaurants in Los Angeles,” we might see different results than someone who lives in Los Angeles and enters the same query. This is because search engines can use our location to customize the results that they provide, showing us relevant results based on our current location. Location queries can be an important tool for finding information on the internet, and they can also help to personalize
Published on: 2021-05-05
Updated on: 2022-06-09