A trio of recently published patent applications from Google, originally filed in 2007, provide a hint at a possible social network from Google, but possibly more importantly give us some insights into how Google might rank objects in social networks such as:
- Media files,
- Articles, and;
Ranking Social Network Objects, invented by Qingshan Luo, Hang Cui, Bo Zhang, and Dong Zhang, and published January 27, 2011, focuses primarily upon how these different objects might be ranked when found in a social network based upon the type of object involved.
When a search engine ranks a web page, a blog post, or a news article, it can look at things like how often certain keywords appear within those documents. It can see how many pages link to those pages, and look at a number of other signals that might help to rank how those appear in search results.
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A Search Engine May Cluster Concepts to Better Understand What Pages are About
Conventional search engines focus upon the words that they find on a web page rather than the meanings of those words. So, when you search for something like [cooking classes Palo Alto], a search engine might look for all of the pages that it can find that include all of those words. If it doesn’t find many, it might do something called “backing off,” and also show some results that don’t include all of the words.
But, chances are that the search engine might not show results for a slightly different version of that search, such as [cooking class palo alto], where “classes” is replaced with “class.” While “class” and “classes” are related with class being a subpart, or stem, of the word classes, sometimes variations of words have very different meanings when used in different contexts.
Google was granted a patent this week that focuses upon more effectively capturing the underlying semantic meaning behind words within text. It builds upon a patent that Google was granted in 2008 which “characterizes a document with respect to clusters of conceptually related words.” It may act to cluster concepts when understanding the text it finds on pages.
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One of the challenges facing someone when they first decide to start a blog is figuring out what to write about, whom to write for, and how to incorporate blogging into their daily routine. This is true for businesses to decide to add a blog to their website as well.
Coming up with a blog content strategy can make those challenges much easier. The first step involves asking yourself why you’re considering blogging, to begin with. Why blog?
Small Business Blogging Objectives
One of the first steps you want to take with a business blog is to define what you want it to achieve. Those may include:
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Back on August 20th of 2010, Google Software Engineer Samarth Keshava published a post titled Showing more results from a domain, telling us:
Today weâ€™ve launched a change to our ranking algorithm that will make it much easier for users to find a large number of results from a single site. For queries that indicate a strong user interest in a particular domain, like [exhibitions at amnh], weâ€™ll now show more results from the relevant site.
The example provided in the post showed seven results from the same museum on a search for exhibits at that museum. He goes on to tell us that in the past, Google would have likely only shown two results from the same domain. In May of 2009, I wrote a post which described when and why Google might show more than two results from the same domain in search results.
My post, Boosting Brands, Businesses, and Other Entities: How a Search Engine Might Assume a Query Implies a Site Search, pointed at a Google patent Query rewriting with entity detection which described when Google might decide to show a number of search results from the same site. The assumption behind that patent was that the intent behind some queries was not so much a request to search the Web for information, but rather was a desire to see specific information from a site closely related to a “named entity” included in the query.
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Microsoft was granted a new patent today, Search ranger system and double-funnel model for search spam analyses and browser protection (US Patent 7,873,635), which provides a detailed look at how Bing might attempt to identify search spammers who redirect traffic from search results pages to pages filled with advertising or other content intended to earn the spammers some money.
The patent uses Google’s Adsense as an example of the kind of advertising that these spammers might use in one of these cloaking schemes.
Ironically, Google’s Matt Cutts also uncovered an interesting Bing affiliate scheme today, from a company that Ad Age calls FaceBook’s third largest advertiser in the third quarter of last year.
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