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Based just outside Philadelphia, Advance Design Interactive offers a full range of Professional Web designs and solutions utilizing Best Practices for Web Development. Starting with discovery, a strategic Internet plan is developed based on your organizational goals, and the website development process includes graphic Web design, logo design, banner design, flash animations, custom programming.

Philadelphia Web Site Design is a new Web Directory dedicated to helping small businesses of the Philadelphia and Pennsylvania region better understand and apply winning Internet marketing strategies. We aim to helping hand in the often confusing worlds of Web Design.

Professional web designer is a Philadelphia Web Design and Development and Search Engine Optimization Company. We focus on Web design and development and Web site marketing services that will generate new business and increase your overall ROI.

PageRank is a probability distribution used to represent the likelihood that a person randomly clicking on links will arrive at any particular page. PageRank can be calculated for any-size collection of documents. It is assumed in several research papers that the distribution is evenly divided between all documents in the collection at the beginning of the computational process. The PageRank computations require several passes, called "iterations", through the collection to adjust approximate PageRank values to more closely reflect the theoretical true value.

A probability is expressed as a numeric value between 0 and 1. A 0.5 probability is commonly expressed as a "50% chance" of something happening. Hence, a PageRank of 0.5 means there is a 50% chance that a person clicking on a random link will be directed to the document with the 0.5 PageRank.

Assume a small universe of four web pages: A, B, C and D. The initial approximation of PageRank would be evenly divided between these four documents. Hence, each document would begin with an estimated PageRank of 0.25.

If pages B, C, and D each only link to A, they would each confer 0.25 PageRank to A. All PageRank PR( ) in this simplistic system would thus gather to A because all links would be pointing to A.

But then suppose page B also has a link to page C, and page D has links to all three pages. The value of the link-votes is divided among all the outbound links on a page. Thus, page B gives a vote worth 0.125 to page A and a vote worth 0.125 to page C. Only one third of D's PageRank is counted for A's PageRank (approximately 0.083).

In other words, the PageRank conferred by an outbound link L( ) is equal to the document's own PageRank score divided by the normalized number of outbound links (it is assumed that links to specific URLs only count once per document).

In the general case, the PageRank value for any page u can be expressed as:

,

PageRank is a link analysis algorithm that assigns a numerical weighting to each element of a hyperlinked set of documents, such as the World Wide Web, with the purpose of "measuring" its relative importance within the set. The algorithm may be applied to any collection of entities with reciprocal quotations and references. The numerical weight that it assigns to any given element E is also called the PageRank of E and denoted by PR(E).

PageRank was developed at Stanford University by Larry Page (hence the name Page-Rank) and later Sergey Brin as part of a research project about a new kind of search engine. The project started in 1995 and led to a functional prototype, named Google, in 1998. Shortly after, Page and Brin founded Google Inc., the company behind the Google search engine. While just one of many factors which determine the ranking of Google search results, PageRank continues to provide the basis for all of Google's web search tools.

The name PageRank is a trademark of Google. The PageRank process has been patented. The patent is not assigned to Google but to Stanford University.

Search engine optimization (SEO) is the process of improving the volume and quality of traffic to a web site from search engines via "natural" ("organic" or "algorithmic") search results. Usually, the earlier a site is presented in the search results, or the higher it "ranks", the more searchers will visit that site. SEO can also target different kinds of search, including image search, local search, and industry-specific vertical search engines.

As a marketing strategy for increasing a site's relevance, SEO considers how search algorithms work and what people search for. SEO efforts may involve a site's coding, presentation, and structure, as well as fixing problems that could prevent search engine indexing programs from fully spidering a site. Other, more noticeable efforts may include adding unique content to a site, ensuring that content is easily indexed by search engine robots, and making the site more appealing to users. Another class of techniques, known as Black Hat SEO or spamdexing, use methods such as link farms and keyword stuffing that tend to harm search engine user experience. Search engines look for sites that employ these techniques and may remove their listings.