Last week, Google published a paper on a way of navigating on touch screens by tracing out alphanumeric characters. For instance, if you have a list of contacts on your screen, and want to move down to a name that begins with the letter L, you would trace an L on your screen. Looking for a song on your playlist, you might handwrite on your screen the first couple of letters from the song title.
The paper is Gesture Search: A Tool for Fast Mobile Data Access (pdf), and it tells us that Gesture Search is presently in use by hundreds of thousands of users, with a mean rating of 4.5 out of 5 for more than 5,000 ratings.
A Google patent application published October 14th, Glyph Entry on Computing Device, provides a number of details that the paper doesn’t, including a look at how this gesture navigation system might be used to navigate maps from Google Maps.
This is the third and final (for now) part in a series on Google Custom Search, and how information from custom search engines might be used in Google’s Web search.
In the first part of this series, SEO and Assumptions behind Web Searches, I described some assumptions search engineers often make that are challenged by a recently published Google patent application, Aggregating Context Data for Programmable Search Engines.
Quickly, those questioned assumptions are:
- Search Engines should avoid using information from external sources in learning how people search
- User data collected about a searcher’s past searches and browsing behavior can help identify the intent of that searcher during new searches
- User data collected about specific searchers, queries, and web sites can also be aggregated to help understand the intent behind a search
If you have the Google Toolbar installed on your browser, you may soon start seeing some odd behavior at times when you click on a search result.
For some pages, Google might deliver you to a page and may display a popup/information box on the bottom right of the page that covers part of the page. That information box may show one or more excerpts of text from one or more parts of the page that are “relevant to your query,” like in the following image:
If you click on one of the text excerpts, your browser will deliver you to the part of the page where that text appears, and possibly highlight the relevant section.
This is the second part of a series on Google Custom Search Engines.
Why spend so much time looking at Google Custom Search? Here are a few reasons which I’ve written about in previous posts:
- Google Subscribed Links, which can be created in Google Custom Search, sometimes appear in Google’s Web Search even if you don’t subscribe to those links.
- Google’s patent describing their Trust Rank approach explores how the kind of labels used as annotations by trusted sources (such as some Custom Search Engine builders) might influence web search results.
- Another patent application from Google explains how labels, which can be created in Google Custom Search, might affect the classification of Web pages by Google, and help to define query refinements that appear above Web search results, as does an additional granted Google Patent describing how Google might be Filtering search results using annotations.
This is the first in a series of posts on Google Custom Search Engines.
If you’re interested in how search works on the Web, you may want to spend some time exploring Google Custom Search. It enables you to create a site search for an individual site, or a customized search engine on specific topics that may focus upon a number of sites that you can select.
There’s another reason to start looking at Google Custom Search Engines, or CSEs. A recently published patent application from Google describes how the Search Engine may use information from CSEs to influence what we might see in Google’s Web search. This post is an introduction to the topic, and it covers how search engines attempt to identify the intent behind queries and web pages.
The patent application, Aggregating Context Data for Programmable Search Engines, includes a fairly well written statement (for a patent application) about one of the difficulties that search engines face when trying to come up with results to show searchers in response to queries. I thought it was worth sharing here, and it provides a nice introduction to a longer exploration of how Google CSEs might be used to improve web search.
Last week, I wrote about a patent granted to Google which described how the search engine may use categories as a search ranking factor to decide whether or not to include some pages in search results for specific queries. The patent was originally filed back in 2004, and focused primarily upon classifying documents based upon things such as the contents of web pages and anchor text in links pointing to pages.
A few days ago, a new patent application was published by Google which focuses upon classification of documents based upon a wider range of information, including user behavior data. Instead of a simple matching of weighted classifications between web pages and queries, the patent filing describes a way of creating profiles for pages which include classification information, and spreading that classification information to unclassified pages through query profiles for queries which both types of pages rank for in search results.
This kind of user-data based profile information could be used along with more conventional ways of ranking pages to improve the quality of search results, and to provide more personalized results to searchers. The patent application is:
Stop, close your eyes, and take a moment to think about your home, without water faucets, without showerheads, without garden hoses, and without toilets. We use water to drink, to clean, to cook, to grow things, to cool our cars, to do countless things that we often take for granted, because we have easy access to one of the most abundant, and most precious resources in the world.
Imagine instead that your only easy access to water was from a dirty irrigation ditch, like in the photo below from a New Mexico back in the 1930s.
Or imagine that you lived in Washington, DC, and your only source of water was a backyard faucet shared by a number of homes, as shown in this image from 1935:
Does Google determine categories for pages and for queries, and can those play a role in how it ranks pages in search results?
Almost everyday, I receive visitors on a query for “bookshelf plans,” on the strength of a past post about Google’s plans for virtual bookshelves in Google library. Most of those visitors probably aren’t surprised that the page is about an online library given the title and snippet appearing for the post, but most of the search results preceeding it describe wooden rather than virtual shelves. My page really doesn’t fit within the same category as the others.
When a search engine determines whether a page is relevant for a certain query, it does more than try to match the text of the query with a page that contains that text, and looking at the links pointing to the page. A Google patent filed in 2004, and granted today describes how the search engine may try to associate web pages with categories, and queries with categories, and come up with a category score for each, to use to rank those pages for categories.
We are told that this kind of category matching addresses a couple of different problems.