Google’s New Patents from IBM

Yesterday I noticed a very large number of new patents listed in the USPTO assignment records for Google from IBM, and made note of them in a post, Google Acquires Over 1,000 IBM Patents in July.

I didn’t expect or anticipate the interest that my post would stir up, though I probably should have, given what seems to be an increased amount of litigation directed at Google involving patent infringement claims, with Apple taking on HTC and Google, Oracle and Google disputing use of Java in Android, Purple Leaf taking exception to Checkout, and other suits.

Given the interest in the IBM patents in a number of places on the web and some conversations I had, I thought it might be a good idea to provide the list of patents that Google acquired earlier this month. Google acquired a number of additional patents from IBM earlier this year and last year as well. I included those in my February post, Google Patents, Updated and Google Self Driving Cars Get Jumpstart from IBM Patents.

In yesterdays’ post, I mentioned that these newly acquired patents cover a wide range of topics, and I’ve had little chance to go through most of them. Some appear to be very broad, while others are much more narrow. Google might find a number of them useful in covering activities they are engaged in presently, such as the manufacture of a very large number of servers. Some include industries that Google might not venture into, such as the fabrication of chips. Many of them might act to help limit litigation aimed at Google.

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Google Acquires Over 1,000 IBM Patents in July

Google was recently involved in a bidding war with Apple, Microsoft, and others over more than 6,000 patent filings from Nortel. It was a war that the search giant lost when a group comprised of Apple, Microsoft, Research in Motion, Ericsson, Sony, and EMC joined together to bid $4.5 billion in cash. Google oddly chose to bid using numbers based upon mathematical formulas and constants, with their final bid based upon pi – $3.14159 billion.

A post at the Official Google Blog, Patents and innovation, by Google’s Senior Vice President and General Counsel Kent Walker in early April discussed patent reform and the need for a company to defend themselves by having a formidable patent portfolio. Google’s decision to pursue the Nortel patents was based in part upon creating a “disincentive for others to sue Google.”

While Google might not have been successful in the auction for Nortel’s intellectual property, they haven’t been standing pat. On July 11th and 12th, Google recorded the assignment of 1,030 granted patents from IBM covering a range of topics, from the fabrication and architecture of memory and microprocessing chips, to other areas of computer architecture including servers and routers as well. A number of the patents also cover relational databases, object oriented programming, and a wide array of business processes.

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Google and Large Scale Data Models Like Panda

Search engine optimization grows and changes much as the Web itself does. With the recent addition of Google Plus to the services that Google offers, and this year’s introduction of the Big Panda updates, one of the growing areas of SEO involves seeing how Google and other search engines might incorporate more user information into how they rank webpages. The introduction of Google Plus has highlighted the importance of looking at how the search engine collects information regarding how people search, how they browser the Web, what they publish online, and how they interact with others in social networks, and what the search engine might do with that information.

With the Panda updates, we’ve seen Google introducing a way of modeling information in large scale data sets, like the Web, to try to identify and predict features of webpages that can be used to rank pages not only on the basis of relevance and popularity (based upon the links pointing to those pages), but also also upon a range of other features such as credibility, trust, originality, range of coverage of a topic, usability, and more.

I’ve been looking back at some of the patents that Google published, and ran into a couple that really weren’t discussed much when they were originally published, and probably should be talked about a little more.

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How Google Might Rank Pages Based upon Usage Information

Historically, search engines have ranked web pages in search results based upon a combination of an information retrieval (IR) score based upon a matching of terms in a query to terms in a document, as well as a linked based score that calculates the quality and quantity of links pointing to a page, based upon a method like PageRank.

A new patent filing from Google explains some shortcomings of these approaches, and explains how a score based upon usage data of a document might be used either in combination with those approaches, or in place of them. The patent tells us that term-based methods can be biased towards pages where the content or display of those pages has been manipulated to focus upon those terms. We’re also told that link-based approaches are limited in that relatively new pages have usually have fewer links pointing to them than older pages, so they often have a lower link-based score.

Instead, pages that are returned as being responsive to a particular query might be assigned a score based upon usage information and ranked based upon those scores, or in combination with IR and link-based scores.

The patent application includes examples of two types of usage data, frequency of visits to a page or site, and number of unique visitors to a page or site, but it tells us that other usage data might be included as well.

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Early Google Circles and the Google Social Site You Might Not Know About

I’ve been doing research on Google’s social Q&A sites codenamed Confucius which are in more than 68 countries and multiple languages, but little known in the US. What I’ve seen includes some tantalizing hints about Google Plus, a description of how content submitted to Google Plus might be ranked in Google Web search, and a possible advertising model for Google Plus that was detailed in a Best Paper nominee at the World Wide Web Conference in North Carolina last year.

I started looking at Confucius a week ago, when I published the post, How Google Might Rank User Generated Web Content in Google & and Other Social Networks. My post describes a ranking signal for user generated content in Web search results, derived from a social network user’s perceived authority on different subjects and the quality of their contributions in interactions on the network, These combined scores might be used as a ranking signal in web search results for the content that user creates. The patent filing was published at the World Intellectual Property Organization website rather than the US patent office website, and the authors of the patent were from Google China, including Edward Y. Chang, the head of Research at Google China, seen in the profile page below:

A social networking profile for Google Research China Head, Edward Y. Chang, showing contacts in a blue circle similar to the circles in Google Plus.

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Google Patent Granted on PageRank Sculpting and Opinion Passing Links

Google filed for a patent in 2005 that could have transformed how we think about and use links, such as letting webmasters decide how much PageRank a link might pass along, or applying machine readable labels to links, indicating that some links might lead to “offensive” content (“offensive=very”) or “funny” information (“funny=somewhat”), or where on a page the destination of a link might appear, such as in a footer or main content area. This patent would also include a method to encrypt the content of some links, so that only certain people might be able to access the information that those links lead to. The patent was granted this week.

When Tim Berners-Lee wrote Links and Law back in 1997, as a commentary on the architecture of the Web, one of the statements that he included was that “The intention in the design of the web was that normal links should simply be references, with no implied meaning.” Before 2005, if you surveyed the links you came across on the Web, you’d often see a combination of anchor text describing the destination of those links and the actual URL of the links in question, but not much in terms of “opinion” about the destinations of those links. At least not something within links that a computer program or a search engine could easily pick up upon.

Starting in 2005, we’ve been seeing additions to the way that links can be written that do express some opinions that search engines can act upon. In an effort to help stop comment spam on blogs, Google, Yahoo, and Microsoft all agreed to not pass along PageRank or link value to sites being linked to when those links included a rel=”nofollow” within them, like in the example below: Continue reading

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How Google Might Rank User Generated Web Content in Google + and Other Social Networks

One of the challenges that face search engines is how to rank content found on sites that rely upon users to create that content, often referred to as User Generated Content or UGC. Towards the end of 2009, I wrote a post about a Yahoo patent that described some of the things they might consider looking at when ranking UGC, in the post How Search Engines May Rank User Generated Content.

With Google’s recent launch of Google Plus, I’m anticipating posts and comments from their new social network system to start appearing in Google Web search results sometime soon.

A Google patent application published this past May at the World Intellectual Property Organization (WIPO) describes possible signals that Google might consider in its Web search results when it displays and ranks images and videos on photo and video sharing sites, questions and answers on Q&A sites, forum posts and responses, blog posts and comments, and social network posts, status updates, and comments. It was originally filed on October 29, 2009, but looks like it could be a system that could be used with Google + without too many modifications. The patent filing hasn’t been published yet at the US Patent and Trademark Office.

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Google’s Second Most Important Algorithm? Before Google’s Panda, there was Phil

They named the project Phil, because it sounded friendly. (For those who required an acronym, they had one handy: Probabilistic Hierarchical Inferential Learner.) That was bad news for a Google Engineer named Phil who kept getting emails about the system. He begged Harik to change the name, but Phil it was.

Steven Levy, In The Plex: How Google Thinks, Works, and Shapes Our Lives.

How does Google decide which Adsense advertisements to show on which Web pages? How do they avoid showing inappropriate advertisements on those content pages? How does the document classification system they use to power those decisions work, and has its use been expanded beyond Google’s advertising system?

A screenshot of an interface from the patent Categorizing objects, such as documents and/or clusters, with respect to a taxonomy and data structures derived from such categorization, that shows how someone might discover which categories a website might be included within.

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Getting Information about Search and SEO Directly from the Search Engines