Interests are very similar to Topics. In fact, they are the same themes. However, the key difference is that Topics target websites and Interests target users. Google gleans user interest based on browsing history or self-selected interests if they’re logged in to their Google account. This allows your ads to appear on whatever site someone with your targeted interests is on, even if that site isn’t related.
When this article was first written, the non-www URL had PR4 due to using different versions of the link URLs within the site. It had the effect of sharing the page’s PageRank between the 2 pages (the 2 versions) and, therefore, between the 2 sites. That’s not the best way to do it. Since then, I’ve tidied up the internal linkages and got the non-www version down to PR1 so that the PageRank within the site mostly stays in the “www.” version, but there must be a site somewhere that links to it without the “www.” that’s causing the PR1.
A navigational page is a simple page on your site that displays the structure of your website, and usually consists of a hierarchical listing of the pages on your site. Visitors may visit this page if they are having problems finding pages on your site. While search engines will also visit this page, getting good crawl coverage of the pages on your site, it's mainly aimed at human visitors.
The PageRank concept is that a page casts votes for one or more other pages. Nothing is said in the original PageRank document about a page casting more than one vote for a single page. The idea seems to be against the PageRank concept and would certainly be open to manipulation by unrealistically proportioning votes for target pages. E.g. if an outbound link, or a link to an unimportant page, is necessary, add a bunch of links to an important page to minimize the effect.
For example, suppose you're a law firm targeting the phrase "divorce attorney" with a broad match ad. Your ad should appear on the results page for the search query "divorce attorney," but it could also show up for the phrases "reasons for divorce," "dui attorney" or "dealing with divorce for children." In these cases, you may be wasting money on irrelevant searches.
Page and Brin's theory is that the most important pages on the Internet are the pages with the most links leading to them. PageRank thinks of links as votes, where a page linking to another page is casting a vote. The idea comes from academia, where citation counts are used to find the importance of researchers and research. The more often a particular paper is cited by other papers, the more important that paper is deemed. 
We will be looking at how to organize links so that certain pages end up with a larger proportion of the PageRank than others. Adding to the page’s existing PageRank through the iterations produces different proportions than when the equation is used as published. Since the addition is not a part of the published equation, the results are wrong and the proportioning isn’t accurate.
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Pay Per Click (or PPC advertising) is a form of paid digital marketing where advertisers pay a fee each time their ad is clicked. The term PPC can apply to paid ads on social media networks, like Facebook, Twitter and LinkedIn. However, today we’ll focus on Google Adwords which helps your ads stand out to search engine users, displaying them at the top and right-hand side of Google’s search engines. We’ll also explore Google Display Network which displays your ads on relevant websites your customers and prospects land on.
As an example, people could previously create many message-board posts with links to their website to artificially inflate their PageRank. With the nofollow value, message-board administrators can modify their code to automatically insert "rel='nofollow'" to all hyperlinks in posts, thus preventing PageRank from being affected by those particular posts. This method of avoidance, however, also has various drawbacks, such as reducing the link value of legitimate comments. (See: Spam in blogs#nofollow)
We will be looking at how to organize links so that certain pages end up with a larger proportion of the PageRank than others. Adding to the page’s existing PageRank through the iterations produces different proportions than when the equation is used as published. Since the addition is not a part of the published equation, the results are wrong and the proportioning isn’t accurate.

Using an omni-channel strategy is becoming increasingly important for enterprises who must adapt to the changing expectations of consumers who want ever-more sophisticated offerings throughout the purchasing journey. Retailers are increasingly focusing on their online presence, including online shops that operate alongside existing store-based outlets. The "endless aisle" within the retail space can lead consumers to purchase products online that fit their needs while retailers do not have to carry the inventory within the physical location of the store. Solely Internet-based retailers are also entering the market; some are establishing corresponding store-based outlets to provide personal services, professional help, and tangible experiences with their products.[24]


By relying so much on factors such as keyword density which were exclusively within a webmaster's control, early search engines suffered from abuse and ranking manipulation. To provide better results to their users, search engines had to adapt to ensure their results pages showed the most relevant search results, rather than unrelated pages stuffed with numerous keywords by unscrupulous webmasters. This meant moving away from heavy reliance on term density to a more holistic process for scoring semantic signals.[13] Since the success and popularity of a search engine is determined by its ability to produce the most relevant results to any given search, poor quality or irrelevant search results could lead users to find other search sources. Search engines responded by developing more complex ranking algorithms, taking into account additional factors that were more difficult for webmasters to manipulate. In 2005, an annual conference, AIRWeb, Adversarial Information Retrieval on the Web was created to bring together practitioners and researchers concerned with search engine optimization and related topics.[14]
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