While some people may take a quick peek at the new Google patent and get quick tired head, the true geeks like to dissect the crazy talk and try to make sense of it. I figured I would put down my thoughts and perception of certain key sections of their new piece of work. Maybe it will help those who feel like their head will explode if they read anymore of this new ranking system. 🙂
Lets do all of ourselves a favor and skip the “claims” and move down to the meat of the patent application labeled Description.
 Both categories of search engines strive to provide high quality results for a search query. There are several factors that may affect the quality of the results generated by a search engine. For example, some web site producers use spamming techniques to artificially inflate their rank. Also, “stale” documents (i.e., those documents that have not been updated for a period of time and, thus, contain stale data) may be ranked higher than “fresher” documents (i.e., those documents that have been more recently updated and, thus, contain more recent data). In some particular contexts, the higher ranking stale documents degrade the search results.
They are saying here that sites can get themselves ranked high with a back link from a high ranked site that is not updated often.
SUMMARY OF THE INVENTION
 Systems and methods consistent with the principles of the invention may score documents based, at least in part, on history data associated with the documents. This scoring may be used to improve search results generated in connection with a search query.
 According to one aspect consistent with the principles of the invention, a method for scoring a document is provided. The method may include identifying a document and obtaining one or more types of history data associated with the document. The method may further include generating a score for the document based, at least in part, on the one or more types of history data.
 According to another aspect, a method for scoring documents is provided. The method may include determining an age of linkage data associated with a linked document and ranking the linked document based on a decaying function of the age of the linkage data.
In this summary, they are implying the scoring of sites will be based on historical information like the age of back links.
 History component 320 may gather history data associated with the documents in document corpus 340. In implementations consistent with the principles of the invention, the history data may include data relating to: document inception dates; document content updates/changes; query analysis; link-based criteria; anchor text (e.g., the text in which a hyperlink is embedded, typically underlined or otherwise highlighted in a document); traffic; user behavior; domain-related information; ranking history; user maintained/generated data (e.g., bookmarks); unique words, bigrams, and phrases in anchor text; linkage of independent peers; and/or document topics. These different types of history data are described in additional detail below. In other implementations, the history data may include additional or different kinds of data.
This is a good section which details the many bits of data that may be included in the scoring of websites.
 Search engine 125 may use the inception date of a document for scoring of the document. For example, it may be assumed that a document with a fairly recent inception date will not have a significant number of links from other documents (i.e., back links). For existing link-based scoring techniques that score based on the number of links to/from a document, this recent document may be scored lower than an older document that has a larger number of links (e.g., back links). When the inception date of the documents are considered, however, the scores of the documents may be modified (either positively or negatively) based on the documents’ inception dates.
 Consider the example of a document with an inception date of yesterday that is referenced by 10 back links. This document may be scored higher by search engine 125 than a document with an inception date of 10 years ago that is referenced by 100 back links because the rate of link growth for the former is relatively higher than the latter. While a spiky rate of growth in the number of back links may be a factor used by search engine 125 to score documents, it may also signal an attempt to spam search engine 125. Accordingly, in this situation, search engine 125 may actually lower the score of a document(s) to reduce the effect of spamming.
These two sections talk of scoring a site based on the age of back links pointing to it. It also talks of scoring based on the rate of back links that are found pointing to the website. In other words, if a brand new site goes from 10 links to 10,000 links in a week, it’s obvious the website is using spamming techniques to increase it’s score and basically lower the score rather than increase it.
 In one implementation, search engine 125 may modify the link-based score of a document as follows:
 where H may refer to the history-adjusted link score, L may refer to the link score given to the document, which can be derived using any known link scoring technique (e.g., the scoring technique described in U.S. Pat. No. 6,285,999) that assigns a score to a document based on links to/from the document, and F may refer to elapsed time measured from the inception date associated with the document (or a window within this period).
 For some queries, older documents may be more favorable than newer ones. As a result, it may be beneficial to adjust the score of a document based on the difference (in age) from the average age of the result set. In other words, search engine 125 may determine the age of each of the documents in a result set (e.g., using their inception dates), determine the average age of the documents, and modify the scores of the documents (either positively or negatively) based on a difference between the documents’ age and the average age.
This illustrates a formula used to get the score. The link score appears to be related to their PageRank, although I have not gone through the related patent since it relates to several others. (Quite a web of patents!) But it appears use an existing score of a website into their new formula using history and link age giving a new score. I’m definitely not a math whiz to break this down, but I’m sure the genius’ will soon follow with their interpretations.
 In one implementation, search engine 125 may generate a content update score (U) as follows:
 U=f(UF, UA),
 where f may refer to a function, such as a sum or weighted sum, UF may refer to an update frequency score that represents how often a document (or page) is updated, and UA may refer to an update amount score that represents how much the document (or page) has changed over time. UF may be determined in a number of ways, including as an average time between updates, the number of updates in a given time period, etc.
 UA may also be determined as a function of one or more factors, such as the number of “new” or unique pages associated with a document over a period of time. Another factor might include the ratio of the number of new or unique pages associated with a document over a period of time versus the total number of pages associated with that document. Yet another factor may include the amount that the document is updated over one or more periods of time (e.g., n % of a document’s visible content may change over a period t (e.g., last m months)), which might be an average value. A further factor might include the amount that the document (or page) has changed in one or more periods of time (e.g., within the last x days).
 UF and UA may be used in other ways to influence the score assigned to a document. For example, the rate of change in a current time period can be compared to the rate of change in another (e.g., previous) time period to determine whether there is an acceleration or deceleration trend. Documents for which there is an increase in the rate of change might be scored higher than those documents for which there is a steady rate of change, even if that rate of change is relatively high. The amount of change may also be a factor in this scoring. For example, documents for which there is an increase in the rate of change when that amount of change is greater than some threshold might be scored higher than those documents for which there is a steady rate of change or an amount of change is less than the threshold.
This part is interesting. It says they will begin scoring the actual content found and the rate of change. There will be two parts, change on a page and change in the amount of pages being added. The key here is, they watch for trends. If you change information every day and add 10 pages of content every day, it will be normal. If another site adds information sporadically and puts a lot of information up over two days and a little over the next few days, that site’s score will be higher. And in , they are all but disregarding everything but the meat of your page. This means links placed on the side or foot of the pages are probably not going to be counted much, if at all. This is a definite cry for our Billboard product! Your links are embedded into the meat of the page, which is what they do count.
 According to yet another implementation, search engine 125 may store a summary or other representation of a document and monitor this information for changes. According to a further implementation, search engine 125 may generate a similarity hash (which may be used to detect near-duplication of a document) for the document and monitor it for changes. A change in a similarity hash may be considered to indicate a relatively large change in its associated document. In other implementations, yet other techniques may be used to monitor documents for changes. In situations where adequate data storage resources exist, the full documents may be stored and used to determine changes rather than some representation of the documents.
I wanted to point this one out for one reason . . . do not duplicate your content! They have mathematical equations that spot this automatically and will ding you for it. There is nothing that will help you by duplicating your content on several pages or different domains. 😉
 According to an implementation consistent with the principles of the invention, one or more query-based factors may be used to generate (or alter) a score associated with a document. For example, one query-based factor may relate to the extent to which a document is selected over time when the document is included in a set of search results. In this case, search engine 125 might score documents selected relatively more often/increasingly by users higher than other documents.
 Another query-based factor may relate to the occurrence of certain search terms appearing in queries over time. A particular set of search terms may increasingly appear in queries over a period of time. For example, terms relating to a “hot” topic that is gaining/has gained popularity or a breaking news event would conceivably appear frequently over a period of time. In this case, search engine 125 may score documents associated with these search terms (or queries) higher than documents not associated with these terms.
In simple terms, if people do not click your listing in results, you’ll slide down. If you are being clicked by people more often, then it will help you. And if your site deals with a hot topic then you will be scored higher than if your site is not directly related to the hot topic.
0062] Yet another query-based factor might relate to the “staleness” of documents returned as search results. The staleness of a document may be based on factors, such as document creation date, anchor growth, traffic, content change, forward/back link growth, etc. For some queries, recent documents are very important (e.g., if searching for Frequently Asked Questions (FAQ) files, the most recent version would be highly desirable). Search engine 125 may learn which queries recent changes are most important for by analyzing which documents in search results are selected by users. More specifically, search engine 125 may consider how often users favor a more recent document that is ranked lower than an older document in the search results. Additionally, if over time a particular document is included in mostly topical queries (e.g., “World Series Champions”) versus more specific queries (e.g., “New York Yankees”), then this query-based factor–by itself or with others mentioned herein–may be used to lower a score for a document that appears to be stale.
 In some situations, a stale document may be considered more favorable than more recent documents. As a result, search engine 125 may consider the extent to which a document is selected over time when generating a score for the document. For example, if for a given query, users over time tend to select a lower ranked, relatively stale, document over a higher ranked, relatively recent document, this may be used by search engine 125 as an indication to adjust a score of the stale document.
 Yet another query-based factor may relate to the extent to which a document appears in results for different queries. In other words, the entropy of queries for one or more documents may be monitored and used as a basis for scoring. For example, if a particular document appears as a hit for a discordant set of queries, this may (though not necessarily) be considered a signal that the document is spam, in which case search engine 125 may score the document relatively lower.
All of this is simply saying their bots will monitor the activity of users. Depending on the behavior of the users, it will score a site high based on staleness or newness. In other words, if in a subject people constantly select older sites, then it will score older sites higher in that subject. And vice versa for the newer sites.
 According to an implementation consistent with the principles of the invention, one or more link-based factors may be used to generate (or alter) a score associated with a document. In one implementation, the link-based factors may relate to the dates that new links appear to a document and that existing links disappear. The appearance date of a link may be the first date that search engine 125 finds the link or the date of the document that contains the link (e.g., the date that the document was found with the link or the date that it was last updated). The disappearance date of a link may be the first date that the document containing the link either dropped the link or disappeared itself.
 These dates may be determined by search engine 125 during a crawl or index update operation. Using this date as a reference, search engine 125 may then monitor the time-varying behavior of links to the document, such as when links appear or disappear, the rate at which links appear or disappear over time, how many links appear or disappear during a given time period, whether there is trend toward appearance of new links versus disappearance of existing links to the document, etc.
 Using the time-varying behavior of links to (and/or from) a document, search engine 125 may score the document accordingly. For example, a downward trend in the number or rate of new links (e.g., based on a comparison of the number or rate of new links in a recent time period versus an older time period) over time could signal to search engine 125 that a document is stale, in which case search engine 125 may decrease the document’s score. Conversely, an upward trend may signal a “fresh” document (e.g., a document whose content is fresh–recently created or updated) that might be considered more relevant, depending on the particular situation and implementation.
This says they will monitor back links for trends. If the trend begins to drop links, the site could be deemed a stale site. If the trend is increasing, it would be scored higher as a freshly updated site. In other words, if you continually build links, you will be fine. If you add a lot of links and stop, then they start dropping off, not so good.
 The dates that links appear can also be used to detect “spam,” where owners of documents or their colleagues create links to their own document for the purpose of boosting the score assigned by a search engine. A typical, “legitimate” document attracts back links slowly. A large spike in the quantity of back links may signal a topical phenomenon (e.g., the CDC web site may develop many links quickly after an outbreak, such as SARS), or signal attempts to spam a search engine (to obtain a higher ranking and, thus, better placement in search results) by exchanging links, purchasing links, or gaining links from documents without editorial discretion on making links. Examples of documents that give links without editorial discretion include guest books, referrer logs, and “free for all” pages that let anyone add a link to a document.
This is an important part stating that natural link building process happens slowly. So building link popularity should be a steady process occuring in small chunks. And definitely don’t waste your time on guestbooks/forums and FFA pages.
 According to another implementation, the analysis may depend, not only on the age of the links to a document, but also on the dynamic-ness of the links. As such, search engine 125 may weight documents that have a different featured link each day, despite having a very fresh link, differently (e.g., lower) than documents that are consistently updated and consistently link to a given target document. In one exemplary implementation, search engine 125 may generate a score for a document based on the scores of the documents with links to the document for all versions of the documents within a window of time. Another version of this may factor a discount/decay into the integration based on the major update times of the document.
This one goes out to all of you participating in the programs like Digital Point’s coop network and also Link Vault. . . Other than possibly getting traffic, which probably isn’t that great since most people stick them in hard to find locations, these programs look like they are not going to help much anymore. They are great free programs to help people out, but of course the big girl (Google) had to put a stop to them. I believe the constant changing of text ads and url’s with every visit is a flag to them and they will either be discounted or ignored all together. Hopefully they will not penalize for them!
 Alternatively, if the content of a document changes such that it differs significantly from the anchor text associated with its back links, then the domain associated with the document may have changed significantly (completely) from a previous incarnation. This may occur when a domain expires and a different party purchases the domain. Because anchor text is often considered to be part of the document to which its associated link points, the domain may show up in search results for queries that are no longer on topic. This is an undesirable result.
 One way to address this problem is to estimate the date that a domain changed its focus. This may be done by determining a date when the text of a document changes significantly or when the text of the anchor text changes significantly. All links and/or anchor text prior to that date may then be ignored or discounted.
This one is a sharp blow to those who hawk over high ranked older sites when they expire. Buying existing sites will be no good unless their topic is directly related to what you plan to put on it after you attain the name. Once they realize the domain changed ownership, all previous links are discounted.
 The freshness of anchor text may also be used as a factor in scoring documents. The freshness of an anchor text may be determined, for example, by the date of appearance/change of the anchor text, the date of appearance/change of the link associated with the anchor text, and/or the date of appearance/change of the document to which the associated link points. The date of appearance/change of the document pointed to by the link may be a good indicator of the freshness of the anchor text based on the theory that good anchor text may go unchanged when a document gets updated if it is still relevant and good. In order to not update an anchor text’s freshness from a minor edit of a tiny unrelated part of a document, each updated document may be tested for significant changes (e.g., changes to a large portion of the document or changes to many different portions of the document) and an anchor text’s freshness may be updated (or not updated) accordingly.
HELLO ROTATING ADS! ! ! ! 🙂 This says the LinkWorth rotating ads are great!
 According to an implementation consistent with the principles of the invention, information relating to traffic associated with a document over time may be used to generate (or alter) a score associated with the document. For example, search engine 125 may monitor the time-varying characteristics of traffic to, or other “use” of, a document by one or more users. A large reduction in traffic may indicate that a document may be stale (e.g., no longer be updated or may be superseded by another document).
 In one implementation, search engine 125 may compare the average traffic for a document over the last j days (e.g., where j=30) to the average traffic during the month where the document received the most traffic, optionally adjusted for seasonal changes, or during the last k days (e.g., where k=365). Optionally, search engine 125 may identify repeating traffic patterns or perhaps a change in traffic patterns over time. It may be discovered that there are periods when a document is more or less popular (i.e., has more or less traffic), such as during the summer months, on weekends, or during some other seasonal time period. By identifying repeating traffic patterns or changes in traffic patterns, search engine 125 may appropriately adjust its scoring of the document during and outside of these periods.
 Additionally, or alternatively, search engine 125 may monitor time-varying characteristics relating to “advertising traffic” for a particular document. For example, search engine 125 may monitor one or a combination of the following factors: (1) the extent to and rate at which advertisements are presented or updated by a given document over time; (2) the quality of the advertisers (e.g., a document whose advertisements refer/link to documents known to search engine 125 over time to have relatively high traffic and trust, such as amazon.com, may be given relatively more weight than those documents whose advertisements refer to low traffic/untrustworthy documents, such as a pornographic site); and (3) the extent to which the advertisements generate user traffic to the documents to which they relate (e.g., their click-through rate). Search engine 125 may use these time-varying characteristics relating to advertising traffic to score the document.
They are scoring sites based on traffic. They watch for seasonal trends and will know to score sites higher during their seasonal times.
 According to an implementation consistent with the principles of the invention, information corresponding to individual or aggregate user behavior relating to a document over time may be used to generate (or alter) a score associated with the document. For example, search engine 125 may monitor the number of times that a document is selected from a set of search results and/or the amount of time one or more users spend accessing the document. Search engine 125 may then score the document based, at least in part, on this information.
 If a document is returned for a certain query and over time, or within a given time window, users spend either more or less time on average on the document given the same or similar query, then this may be used as an indication that the document is fresh or stale, respectively. For example, assume that the query “Riverview swimming schedule” returns a document with the title “Riverview Swimming Schedule.” Assume further that users used to spend 30 seconds accessing it, but now every user that selects the document only spends a few seconds accessing it. Search engine 125 may use this information to determine that the document is stale (i.e., contains an outdated swimming schedule) and score the document accordingly.
Make sure you keep your users reading your info as long as possible! If people leave your site faster each time, it will go against you considering your site stale.
 According to an implementation consistent with the principles of the invention, information relating to a domain associated with a document may be used to generate (or alter) a score associated with the document. For example, search engine 125 may monitor information relating to how a document is hosted within a computer network (e.g., the Internet, an intranet or other network or database of documents) and use this information to score the document.
 Individuals who attempt to deceive (spam) search engines often use throwaway or “doorway” domains and attempt to obtain as much traffic as possible before being caught. Information regarding the legitimacy of the domains may be used by search engine 125 when scoring the documents associated with these domains.
 Certain signals may be used to distinguish between illegitimate and legitimate domains. For example, domains can be renewed up to a period of 10 years. Valuable (legitimate) domains are often paid for several years in advance, while doorway (illegitimate) domains rarely are used for more than a year. Therefore, the date when a domain expires in the future can be used as a factor in predicting the legitimacy of a domain and, thus, the documents associated therewith.
 Also, or alternatively, the domain name server (DNS) record for a domain may be monitored to predict whether a domain is legitimate. The DNS record contains details of who registered the domain, administrative and technical addresses, and the addresses of name servers (i.e., servers that resolve the domain name into an IP address). By analyzing this data over time for a domain, illegitimate domains may be identified. For instance, search engine 125 may monitor whether physically correct address information exists over a period of time, whether contact information for the domain changes relatively often, whether there is a relatively high number of changes between different name servers and hosting companies, etc. In one implementation, a list of known-bad contact information, name servers, and/or IP addresses may be identified, stored, and used in predicting the legitimacy of a domain and, thus, the documents associated therewith.
 Also, or alternatively, the age, or other information, regarding a name server associated with a domain may be used to predict the legitimacy of the domain. A “good” name server may have a mix of different domains from different registrars and have a history of hosting those domains, while a “bad” name server might host mainly pornography or doorway domains, domains with commercial words (a common indicator of spam), or primarily bulk domains from a single registrar, or might be brand new. The newness of a name server might not automatically be a negative factor in determining the legitimacy of the associated domain, but in combination with other factors, such as ones described herein, it could be.
This claims they will be learning DNS information on each domain, including nameservers, ip addresses and where the domains were registered.
 In addition, or alternatively, search engine 125 may monitor the ranks of documents over time to detect sudden spikes in the ranks of the documents. A spike may indicate either a topical phenomenon (e.g., a hot topic) or an attempt to spam search engine 125 by, for example, trading or purchasing links. Search engine 125 may take measures to prevent spam attempts by, for example, employing hysteresis to allow a rank to grow at a certain rate. In another implementation, the rank for a given document may be allowed a certain maximum threshold of growth over a predefined window of time. As a further measure to differentiate a document related to a topical phenomenon from a spam document, search engine 125 may consider mentions of the document in news articles, discussion groups, etc. on the theory that spam documents will not be mentioned, for example, in the news. Any or a combination of these techniques may be used to curtail spamming attempts.
This section proves that buying links based solely on high pagerank is not the way to go. The mixture will cause a more natural increase of your ranking. . . something they want to see.
 It may be possible for search engine 125 to make exceptions for documents that are determined to be authoritative in some respect, such as government documents, web directories (e.g., Yahoo), and documents that have shown a relatively steady and high rank over time. For example, if an unusual spike in the number or rate of increase of links to an authoritative document occurs, then search engine 125 may consider such a document not to be spam and, thus, allow a relatively high or even no threshold for (growth of) its rank (over time).
This simply states acquiring links from big directories like Yahoo and so on is fine. A bit hypocritical, don’t you think?! You can pay for it with big companies, but you can’t pay for it from small companies. hmmm. . .
 According to an implementation consistent with the principles of the invention, user maintained or generated data may be used to generate (or alter) a score associated with a document. For example, search engine 125 may monitor data maintained or generated by a user, such as “bookmarks,” “favorites,” or other types of data that may provide some indication of documents favored by, or of interest to, the user. Search engine 125 may obtain this data either directly (e.g., via a browser assistant) or indirectly (e.g., via a browser). Search engine 125 may then analyze over time a number of bookmarks/favorites to which a document is associated to determine the importance of the document.
 Search engine 125 may also analyze upward and downward trends to add or remove the document (or more specifically, a path to the document) from the bookmarks/favorites lists, the rate at which the document is added to or removed from the bookmarks/favorites lists, and/or whether the document is added to, deleted from, or accessed through the bookmarks/favorites lists. If a number of users are adding a particular document to their bookmarks/favorites lists or often accessing the document through such lists over time, this may be considered an indication that the document is relatively important. On the other hand, if a number of users are decreasingly accessing a document indicated in their bookmarks/favorites list or are increasingly deleting/replacing the path to such document from their lists, this may be taken as an indication that the document is outdated, unpopular, etc. Search engine 125 may then score the documents accordingly.
 In an alternative implementation, other types of user data that may indicate an increase or decrease in user interest in a particular document over time may be used by search engine 125 to score the document. For example, the “temp” or cache files associated with users could be monitored by search engine 125 to identify whether there is an increase or decrease in a document being added over time. Similarly, cookies associated with a particular document might be monitored by search engine 125 to determine whether there is an upward or downward trend in interest in the document.
Now is a good time to add the “ADD US TO YOUR BOOKMARK” options. They will consider this as a positive to your score.
 According to an implementation consistent with the principles of the invention, information regarding unique words, bigrams, and phrases in anchor text may be used to generate (or alter) a score associated with a document. For example, search engine 125 may monitor web (or link) graphs and their behavior over time and use this information for scoring, spam detection, or other purposes. Naturally developed web graphs typically involve independent decisions. Synthetically generated web graphs, which are usually indicative of an intent to spam, are based on coordinated decisions, causing the profile of growth in anchor words/bigrams/phrases to likely be relatively spiky.
 One reason for such spikiness may be the addition of a large number of identical anchors from many documents. Another possibility may be the addition of deliberately different anchors from a lot of documents. Search engine 125 may monitor the anchors and factor them into scoring a document to which their associated links point. For example, search engine 125 may cap the impact of suspect anchors on the score of the associated document. Alternatively, search engine 125 may use a continuous scale for the likelihood of synthetic generation and derive a multiplicative factor to scale the score for the document.
 In summary, search engine 125 may generate (or alter) a score associated with a document based, at least in part, on information regarding unique words, bigrams, and phrases in anchor text associated with one or more links pointing to the document.
This just says, DON’T SPAM!. This talks about machine generated pages that really have no content but only keyword/anchor text happy pages.
 According to an implementation consistent with the principles of the invention, information regarding linkage of independent peers (e.g., unrelated documents) may be used to generate (or alter) a score associated with a document.
 A sudden growth in the number of apparently independent peers, incoming and/or outgoing, with a large number of links to individual documents may indicate a potentially synthetic web graph, which is an indicator of an attempt to spam. This indication may be strengthened if the growth corresponds to anchor text that is unusually coherent or discordant. This information can be used to demote the impact of such links, when used with a link-based scoring technique, either as a binary decision item (e.g., demote the score by a fixed amount) or a multiplicative factor.
This is telling us to stay relevant! Don’t plaster your text link ads all over non-relevant sites. There are definitely situations where a non-relevant site is actually relevant, but keep the majority relevant.
In conclusion, this new patent, which is said to be implemented during this most recent update, is definitely involving some big changes in scoring websites. The underlying goal of this patent is to combat the various types of techniques people use to alter their results. There is no doubt they need to work on many of these forms of spamming, but they also might be taking things to the extreme in some situations. Many of their theories do fit in many situations, however, there are also many situations where their theories go against the grain of certain markets. Although they include that their machine will adapt and “learn” the trends and patterns to eliminate these situations, there is no doubt innocent websites will be hit and hit hard for their over bearing attempts.
Now I can’t fault them for continuing to innovate and strive for the “perfect results”, but it’s almost as if they are focusing more on spammers than they are on relevancy. Ok, so let’s say they successfully eliminate all aspects of spam sites (which will NEVER happen), does this automatically give them the perfect natural listing results? The answer is very easy, which wouldn’t take 4 hours to read like this patent app, the answer is “NO”.
Finally, what does this mean to LinkWorth? “Nothing!” LinkWorth does sell text ads, but guess who else sells text links? Google. It’s a proven method of online marketing and our advertisers are wonderfully excited with the results we present to them. LinkWorth does not use spamming techniques since we match advertisers to relevant partners. If we focused on rankings only, we obviously would not stay in business long with constant changing. Soon we will launch or additional services which will include pay per click management, banner ads and a couple of very exciting new products unheard of by the public! We will change as quick, or quicker, than the search engine themselves. Staying ahead of the curve is what makes or breaks companies and we pride ourselves in staying ahead. Two of our products, Billboards and Rotating Ads, directly benefit from this latest patent addition, so we’re just fine. Sticking to the straight and narrow path will allow companies to live long and healthy lives.