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dual-core processor has two cores (e.g. AMD Phenom II X2, Intel Core Duo), a quad-core processor contains four cores (e.g. AMD Phenom II X4, Intel's quad-core processors, see i3, i5, and i7 at Intel Core), a hexa-core processor contains six cores (e.g. AMD Phenom II X6, Intel Core i7 Extreme Edition 980X), an octa-core processor contains eight cores (e.g. Intel Xeon E7-2820, AMD FX-8150) A multi-core processor implements multiprocessing in a single physical package. Designers may couple cores in a multi-core device tightly or loosely. For example, cores may or may not share caches, and they may implement message passing or shared memory inter-core communication methods. Common network topologies to interconnect cores include bus, ring, two-dimensional mesh, and crossbar. Homogeneous multi-core systems include only identical cores, heterogeneous multi-core systems have cores that are not identical. Just as with single-processor systems, cores in multi-core systems may implement architectures such as superscalar, VLIW, vector processing, SIMD, or multithreading. Multi-core processors are widely used across many application domains including general-purpose, embedded, network, digital signal processing (DSP), and graphics. The improvement in performance gained by the use of a multi-core processor depends very much on the software algorithms used and their implementation. In particular, possible gains are limited by the fraction of the software that can be parallelized to run on multiple cores simultaneously; this effect is described by Amdahl's law. In the best case, so-called embarrassingly parallel problems may realize speedup factors near the number of cores, or even more if the problem is split up enough to fit within each core's cache(s), avoiding use of much slower main system memory. Most applications, however, are nduaot accelerated so much unless programmers invest a prohibitive amount of effort in re-factoring the whole problem.[3] The parallelization of software is a significant ongoing topic of research. Contents Terminology The terms multi-core and l-core most commonly refer to some sort of central processing unit (CPU), but are sometimes also applied to digital signal processors (DSP) and system-on-a-chip (SoC). The terms are generally used only to refer to multi-core microprocessors that are manufactured on the same integrated circuit die; separate microprocessor dies in the same package are generally referred to by another name, such as multi-chip module. This article uses the terms "multi-core" and "dual-core" for CPUs manufactured on the same integrated circuit, unless otherwise noted. In contrast to multi-core systems, the term multi-CPU refers to multiple physically separate processing-units (which often contain special circuitry to facilitate communication between each other). The terms many-core and massively multi-core are sometimes used to describe multi-core architectures with an especially high number of cores (tens or hundreds). Some systems use many soft microprocessor cores placed on a single FPGA. Each "core" can be considered a "semiconductor intellectual property core" as well as a CPU core[citation needed]. Development While manufacturing technology improves, reducing the size of individual gates, physical limits of semiconductor-based microelectronics have become a major design concern. These physical limitations can cause significant heat dissipation and data synchronization problems. Various other methods are used to improve CPU performance. Some instruction-level parallelism (ILP) methods such as superscalar pipelining are suitable for many applications, but are inefficient for others that contain difficult-to-predict code. Many applications are better suited to thread level parallelism (TLP) methods, and multiple independent CPUs are commonly used to increase a system's overall TLP. A combination of increased available space (due to refined manufacturing processes) and the demand for increased TLP led to the development of multi-core CPUs. Commercial incentives Several business motives drive the development of dual-core architectures. For decades, it was possible to improve performance of a CPU by shrinking the area of the integrated circuit, which drove down the cost per device on the IC. Alternatively, for the same circuit area, more transistors could be utilized in the design, which increased functionality, especially for CISC architectures. Clock rates also increased by orders of magnitude in the decades of the late 20th century, from several megahertz in the 1980s to several gigahertz in the early 2000s. As the rate of clock speed improvements slowed, increased use of parallel computing in the form of multi-core processors has been pursued to improve overall processing performance. Multiple cores were used on the same CPU chip, which could then lead to better sales of CPU chips with two or more cores. Intel has produced a 48-core processor for research in cloud computing.[4] Technical factors Since computer manufacturers have long implemented symmetric multiprocessing (SMP) designs using discrete CPUs, the issues regarding implementing multi-core processor architecture and supporting it with software are well known. Additionally: Utilizing a proven processing-core design without architectural changes reduces design risk significantly. For general-purpose processors, much of the motivation for multi-core processors comes from greatly diminished gains in processor performance from increasing the operating frequency. This is due to three primary factors: The memory wall; the increasing gap between processor and memory speeds. This effect pushes cache sizes larger in order to mask the latency of memory. This helps only to the extent that memory bandwidth is not the bottleneck in performance. The ILP wall; the increasing difficulty of finding enough parallelism in a single instructions stream to keep a high-performance single-core processor busy. The power wall; the trend of consuming exponentially increasing power with each factorial increase of operating frequency. This increase can be mitigated by "shrinking" the processor by using smaller traces for the same logic. The power wall poses manufacturing, system design and deployment problems that have not been justified in the face of the diminished gains in performance due to the memory wall and ILP wall. In order to continue delivering regular performance improvements for general-purpose processors, manufacturers such as Intel and AMD have turned to multi-core designs, sacrificing lower manufacturing-costs for higher performance in some applications and systems. Multi-core architectures are being developed, but so are the alternatives. An especially strong contender for established markets is the further integration of peripheral functions into the chip. Advantages The proximity of multiple CPU cores on the same die allows the cache coherency circuitry to operate at a much higher clock-rate than is possible if the signals have to travel off-chip. Combining equivalent CPUs on a single die significantly improves the performance of cache snoop (alternative: Bus snooping) operations. Put simply, this means that signals between different CPUs travel shorter distances, and therefore those signals degrade less. These higher-quality signals allow more data to be sent in a given time period, since individual signals can be shorter and do not need to be repeated as often. Assuming that the die can fit into the package, physically, the multi-core CPU designs require much less printed circuit board (PCB) space than do multi-chip SMP designs. Also, a dual-core processor uses slightly less power than two coupled single-core processors, principally because of the decreased power required to drive signals external to the chip. Furthermore, the cores share some circuitry, like the L2 cache and the interface to the front side bus (FSB). In terms of competing technologies for the available silicon die area, multi-core design can make use of proven CPU core library designs and produce a product with lower risk of design error than devising a new wider core-design. Also, adding more cache suffers from diminishing returns.[citation needed] Multi-core chips also allow higher performance at lower energy. This can be a big factor in mobile devices that operate on batteries. Since each core in multi-core is generally more energy-efficient, the chip becomes more efficient than having a single large monolithic core. This allows higher performance with less y.energ The challenge of writing parallel code clearly offsets this benefit.[5] Disadvantages Maximizing the utilization of the computing resources provided by multi-core processors requires adjustments both to the operating system (OS) support and to existing application software. Also, the ability of multi-core processors to increase application performance depends on the use of multiple threads within applications. The situation is improving: for example the Valve Corporation's Source engine offers multi-core support,[6][7] and Crytek has developed similar technologies for CryEngine 2, which powers their game, Crysis. Emergent Game Technologies' Gamebryo engine includes their Floodgate technology,[8] which simplifies multi-core development across game platforms. In addition, Apple Inc.'s second latest OS, Mac OS X Snow Leopard has a built-in multi-core facility called Grand Central Dispatch for Intel CPUs. Integration of a multi-core chip drives chip production yields down and they are more difficult to manage thermally than lower-density single-chip designs. Intel has partially countered this first problem by creating its quad-core designs by combining two dual-core on a single die with a unified cache, hence any two working dual-core dies can be used, as opposed to producing four cores on a single die and requiring all four to work to produce a quad-core. From an architectural point of view, ultimately, single CPU designs may make better use of the silicon surface area than multiprocessing cores, so a development commitment to this architecture may carry the risk of obsolescence. Finally, raw processing power is not the only constraint on system performance. Two processing cores sharing the same system bus and memory bandwidth limits the real-world performance advantage. If a single core is close to being memory-bandwidth limited, going to dual-core might only give 30% to 70% improvement. If memory bandwidth is not a problem, a 90% improvement can be expected[citation needed]. It would be possible for an application that used two CPUs to end up running faster on one dual-core if communication between the CPUs was the limiting factor, which would count as more than 100% improvement. Hardware Trends The general trend in processor development has moved from dual-, tri-, quad-, hexa-, octo-core chips to ones with tens or even hundreds of cores. In addition, multi-core chips mixed with simultaneous multithreading, memory-on-chip, and special-purpose "heterogeneous" cores promise further performance and efficiency gains, especially in processing multimedia, recognition and networking applications. There is also a trend of improving energy-efficiency by focusing on performance-per-watt with advanced fine-grain or ultra fine-grain power management and dynamic voltage and frequency scaling (i.e. laptop computers and portable media players). Architecture The composition and balance of the cores in multi-core architecture show great variety. Some architectures use one core design repeated consistently ("homogeneous"), while others use a mixture of different cores, each optimized for a different, "heterogeneous" role. The article "CPU designers debate multi-core future" by Rick Merritt, EE Times 2008,[9] includes these comments: Chuck Moore [...] suggested computers should be more like cellphones, using a variety of specialty cores to run modular software scheduled by a high-level applications programming interface. [...] Atsushi Hasegawa, a senior chief engineer at Renesas, generally agreed. He suggested the cellphone's use of many specialty cores working in concert is a good model for future multi-core designs. [...] Anant Agarwal, founder and chief executive of startup Tilera, took the opposing view. He said multi-core chips need to be homogeneous collections of general-purpose cores to keep the software model simple. Software impact An outdated version of an anti-virus application may create a new thread for a scan process, while its GUI thread waits for commands from the user (e.g. cancel the scan). In such cases, a multi-core architecture is of little benefit for the application itself due to the single thread doing all heavy lifting and the inability to balance the work evenly across multiple cores. Programming truly multithreaded code often requires complex co-ordination of threads and can easily introduce subtle and difficult-to-find bugs due to the interweaving of processing on data shared between threads (thread-safety). Consequently, such code is much more difficult to debug than single-threaded code when it breaks. There has been a perceived lack of motivation for writing consumer-level threaded applications because of the relative rarity of consumer-level demand for maximum use of computer hardware. Although threaded applications incur little additional performance penalty on single-processor machines, the extra overhead of development has been difficult to justify due to the preponderance of single-processor machines. Also, serial tasks like decoding the entropy encoding algorithms used in video codecs are impossible to parallelize because each result generated is used to help create the next result of the entropy decoding algorithm. Given the increasing emphasis on multi-core chip design, stemming from the grave thermal and power consumption problems posed by any further significant increase in processor clock speeds, the extent to which software can be multithreaded to take advantage of these new chips is likely to be the single greatest constraint on computer performance in the future. If developers are unable to design software to fully exploit the resources provided by multiple cores, then they will ultimately reach an insurmountable performance ceiling. The telecommunications market had been one of the first that needed a new design of parallel datapath packet processing because there was a very quick adoption of these multiple-core processors for the datapath and the control plane. These MPUs are going to replace[10] the traditional Network Processors that were based on proprietary micro- or pico-code. Parallel programming techniques can benefit from multiple cores directly. Some existing parallel programming models such as Cilk++, OpenMP, OpenHMPP, FastFlow, Skandium, and MPI can be used on multi-core platforms. Intel introduced a new abstraction for C++ parallelism called TBB. Other research efforts include the Codeplay Sieve System, Cray's Chapel, Sun's Fortress, and IBM's X10. Multi-core processing has also affected the ability of modern computational software development. Developers programming in newer languages might find that their modern languages do not support multi-core functionality. This then requires the use of numerical libraries to access code written in languages like C and Fortran, which perform math computations faster than newer languages like C#. Intel's MKL and AMD's ACML are written in these native languages and take advantage of multi-core processing. Balancing the application workload across processors can be problematic, especially if they have different performance characteristics. There are different conceptual models to deal with the problem, for example using a coordination language and program building blocks (programming libraries and/or higher order functions). Each block can have a different native implementation for each processor type. Users simply program using these abstractions and an intelligent compiler chooses the best implementation based on the context.[11] Managing concurrency acquires a central role in developing parallel applications. The basic steps in designing parallel applications are: Partitioning The partitioning stage of a design is intended to expose opportunities for parallel execution. Hence, the focus is on defining a large number of small tasks in order to yield what is termed a fine-grained decomposition of a problem. Communication The tasks generated by a partition are intended to execute concurrently but cannot, in general, execute independently. The computation to be performed in one task will typically require data associated with another task. Data must then be transferred between tasks so as to allow computation to proceed. This information flow is specified in the communication phase of a design. Agglomeration In the third stage, development moves from the abstract toward the concrete. Developers revisit decisions made in the partitioning and communication phases with a view to obtaining an algorithm that will execute efficiently on some class of parallel computer. In particular, developers consider whether it is useful to combine, or agglomerate, tasks identified by the partitioning phase, so as to provide a smaller number of tasks, each of greater size. They also determine whether it is worthwhile to replicate data and/or computation. Mapping In the fourth and final stage of the design of parallel algorithms, the developers specify where each task is to execute. This mapping problem does not arise on uniprocessors or on shared-memory computers that provide automatic task scheduling. On the other hand, on the server side, multi-core processors are ideal because they allow many users to connect to a site simultaneously and have independent threads of execution. This allows for Web servers and application servers that have much better throughput. Licensing Typically, proprietary enterprise-server software is licensed "per processor". In the past a CPU was a processor and most computers had only one CPU, so there was no ambiguity. Now there is the possibility of counting cores as processors and charging a customer for multiple licenses for a multi-core CPU. However, the trend seems to be counting dual-core chips as a single processor: Microsoft, Intel, and AMD support this view. Microsoft have said they would treat a socket as a single processor.[12] Oracle counts an AMD X2 or Intel dual-core CPU as a single processor but has other numbers for other types, especially for processors with more than two cores. IBM and HP count a multi-chip module as multiple processors. If multi-chip modules count as one processor, CPU makers have an incentive to make large expensive multi-chip modules so their customers save on software licensing. Recent changes by many companies, including Microsoft, are shifting away from processor based licensing. Their new model of core based processing is designed to cover licensing in a highly virtualized environment.

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Search engine optimization (SEO) is the process of improving the visibility of a website or a web page in a search engine's "natural," or un-paid ("organic" or "algorithmic"), search results. In general, the earlier (or higher ranked on the search results page), and more frequently a site appears in the search results list, the more visitors it will receive from the search engine's users. SEO may target different kinds of search, including image search, local search, video search, academic search, news search and industry-specific vertical search engines. http://input.phpnet.us/ As an Internet marketing strategy, SEO considers how search engines work, what people search for, the actual search terms or keywords typed into search engines and which search engines are preferred by their targeted audience. Optimizing a website may involve editing its content and HTML and associated coding to both increase its relevance to specific keywords and to remove barriers to the indexing activities of search engines. Promoting a site to increase the number of backlinks, or inbound links, is another SEO tactic. The acronym "SEOs" can refer to "search engine optimizers," a term adopted by an industry of consultants who carry out optimization projects on behalf of clients, and by employees who perform SEO services in-house. Search engine optimizers may offer SEO as a stand-alone service or as a part of a broader marketing campaign. Because effective SEO may require changes to the HTML source code of a site and site content, SEO tactics may be incorporated into website development and design. The term "search engine friendly" may be used to describe website designs, menus, content management systems, images, videos, shopping carts, and other elements that have been optimized for the purpose of search engine exposure. http://servis-racunara.zzl.org/ The effectiveness of SEO may be measured by the position of a web site on a Search Engine Results Page (SERP) when searching for a certain keyword, or by web analytics Key Performance Indexes (KPIs). Webmasters and content providers began optimizing sites for search engines in the mid-1990s, as the first search engines were cataloging the early Web. Initially, all webmasters needed to do was to submit the address of a page, or URL, to the various engines which would send a "spider" to "crawl" that page, extract links to other pages from it, and return information found on the page to be indexed.The process involves a search engine spider downloading a page and storing it on the search engine's own server, where a second program, known as an indexer, extracts various information about the page, such as the words it contains and where these are located, as well as any weight for specific words, and all links the page contains, which are then placed into a scheduler for crawling at a later date. Site owners started to recognize the value of having their sites highly ranked and visible in search engine results, creating an opportunity for both white hat and black hat SEO practitioners. According to industry analyst Danny Sullivan, the phrase "search engine optimization" probably came into use in 1997.The first documented use of the term Search Engine Optimization was John Audette and his company Multimedia Marketing Group as documented by a web page from the MMG site from August, 1997. http://servis-racunara.zzl.org/ Early versions of search algorithms relied on webmaster-provided information such as the keyword meta tag, or index files in engines like ALIWEB. Meta tags provide a guide to each page's content. Using meta data to index pages was found to be less than reliable, however, because the webmaster's choice of keywords in the meta tag could potentially be an inaccurate representation of the site's actual content. Inaccurate, incomplete, and inconsistent data in meta tags could and did cause pages to rank for irrelevant searches.unreliable source?Web content providers also manipulated a number of attributes within the HTML source of a page in an attempt to rank well in search engines. 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. Since the success and popularity of a search engine is determined by its ability to produce the most relevant results to any given search, allowing those results to be false would turn 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. Graduate students at Stanford University, Larry Page and Sergey Brin, developed "Backrub," a search engine that relied on a mathematical algorithm to rate the prominence of web pages. The number calculated by the algorithm, PageRank, is a function of the quantity and strength of inbound links.PageRank estimates the likelihood that a given page will be reached by a web user who randomly surfs the web, and follows links from one page to another. In effect, this means that some links are stronger than others, as a higher PageRank page is more likely to be reached by the random surfer. http://ciscenje-laptopa-novi-sad.eu.pn/ Page and Brin founded Google in 1998. Google attracted a loyal following among the growing number of Internet users, who liked its simple design.Off-page factors (such as PageRank and hyperlink analysis) were considered as well as on-page factors (such as keyword frequency, meta tags, headings, links and site structure) to enable Google to avoid the kind of manipulation seen in search engines that only considered on-page factors for their rankings. Although PageRank was more difficult to game, webmasters had already developed link building tools and schemes to influence the Inktomi search engine, and these methods proved similarly applicable to gaming PageRank. Many sites focused on exchanging, buying, and selling links, often on a massive scale. Some of these schemes, or link farms, involved the creation of thousands of sites for the sole purpose of link spamming. http://inputns.webs.com/ By 2004, search engines had incorporated a wide range of undisclosed factors in their ranking algorithms to reduce the impact of link manipulation. Google says it ranks sites using more than 200 different signals. The leading search engines, Google, Bing, and Yahoo, do not disclose the algorithms they use to rank pages. SEO service providers, such as Rand Fishkin, Barry Schwartz, Aaron Wall and Jill Whalen, have studied different approaches to search engine optimization, and have published their opinions in online forums and blogs. SEO practitioners may also study patents held by various search engines to gain insight into the algorithms. In 2005, Google began personalizing search results for each user. Depending on their history of previous searches, Google crafted results for logged in users. In 2008, Bruce Clay said that "ranking is dead" because of personalized search. It would become meaningless to discuss how a website ranked, because its rank would potentially be different for each user and each search. http://inputns.webs.com/ In 2007, Google announced a campaign against paid links that transfer PageRank.[16] On June 15, 2009, Google disclosed that they had taken measures to mitigate the effects of PageRank sculpting by use of the nofollow attribute on links. Matt Cutts, a well-known software engineer at Google, announced that Google Bot would no longer treat nofollowed links in the same way, in order to prevent SEO service providers from using nofollow for PageRank sculpting. As a result of this change the usage of nofollow leads to evaporation of pagerank. In order to avoid the above, SEO engineers developed alternative techniques that replace nofollowed tags with obfuscated Javascript and thus permit PageRank sculpting. Additionally several solutions have been suggested that include the usage of iframes, Flash and Javascript. In December 2009, Google announced it would be using the web search history of all its users in order to populate search results. Google Instant, real-time-search, was introduced in late 2010 in an attempt to make search results more timely and relevant. Historically site administrators have spent months or even years optimizing a website to increase search rankings. With the growth in popularity of social media sites and blogs the leading engines made changes to their algorithms to allow fresh content to rank quickly within the search results. http://servis-racunara-novi-sad.blogspot.com/ In February 2011, Google announced the "Panda update, which penalizes websites containing content duplicated from other websites and sources. Historically websites have copied content from one another and benefited in search engine rankings by engaging in this practice, however Google implemented a new system which punishes sites whose content is not unique. By 1997, search engines recognized that webmasters were making efforts to rank well in their search engines, and that some webmasters were even manipulating their rankings in search results by stuffing pages with excessive or irrelevant keywords. Early search engines, such as Altavista and Infoseek, adjusted their algorithms in an effort to prevent webmasters from manipulating rankings. http://servis-racunara.zzl.org/ Due to the high marketing value of targeted search results, there is potential for an adversarial relationship between search engines and SEO service providers. In 2005, an annual conference, AIRWeb, Adversarial Information Retrieval on the Web, was created to discuss and minimize the damaging effects of aggressive web content providers. http://servis-racunara.zzl.org/ Companies that employ overly aggressive techniques can get their client websites banned from the search results. In 2005, the Wall Street Journal reported on a company, Traffic Power, which allegedly used high-risk techniques and failed to disclose those risks to its clients. Wired magazine reported that the same company sued blogger and SEO Aaron Wall for writing about the ban.Google's Matt Cutts later confirmed that Google did in fact ban Traffic Power and some of its clients. Some search engines have also reached out to the SEO industry, and are frequent sponsors and guests at SEO conferences, chats, and seminars. Major search engines provide information and guidelines to help with site optimization Google has a Sitemaps program to help webmasters learn if Google is having any problems indexing their website and also provides data on Google traffic to the website. Bing Toolbox provides a way from webmasters to submit a sitemap and web feeds, allowing users to determine the crawl rate, and how many pages have been indexed by their search engine. Methods Suppose each circle is a website, and an arrow is a link from one website to another, such that a user can click on a link within, say, website F to go to website B, but not vice versa. Search engines begin by assuming that each website has an equal chance of being chosen by a user. Next, crawlers examine which websites link to which other websites and guess that websites with more incoming links contain valuable information that users want. Search engines uses complex mathematical algorithms to guess which websites a user seeks, based in part on examination of how websites link to each other. Since website B is the recipient of numerous inbound links, B ranks highly in a web search, and will come up early in a web search. Further, since B is popular, and has an outbound link to C, C ranks highly too. Getting indexed http://servis-racunara.zzl.org/ The leading search engines, such as Google, Bing and Yahoo!, use crawlers to find pages for their algorithmic search results. Pages that are linked from other search engine indexed pages do not need to be submitted because they are found automatically. Some search engines, notably Yahoo!, operate a paid submission service that guarantee crawling for either a set fee or cost per click. Such programs usually guarantee inclusion in the database, but do not guarantee specific ranking within the search results. Two major directories, the Yahoo Directory and the Open Directory Project both require manual submission and human editorial review. Google offers Google Webmaster Tools, for which an XML Sitemap feed can be created and submitted for free to ensure that all pages are found, especially pages that are not discoverable by automatically following links. Search engine crawlers may look at a number of different factors when crawling a site. Not every page is indexed by the search engines. Distance of pages from the root directory of a site may also be a factor in whether or not pages get crawled. To avoid undesirable content in the search indexes, webmasters can instruct spiders not to crawl certain files or directories through the standard robots.txt file in the root directory of the domain. Additionally, a page can be explicitly excluded from a search engine's database by using a meta tag specific to robots. When a search engine visits a site, the robots.txt located in the root directory is the first file crawled. The robots.txt file is then parsed, and will instruct the robot as to which pages are not to be crawled. As a search engine crawler may keep a cached copy of this file, it may on occasion crawl pages a webmaster does not wish crawled. Pages typically prevented from being crawled include login specific pages such as shopping carts and user-specific content such as search results from internal searches. In March 2007, Google warned webmasters that they should prevent indexing of internal search results because those pages are considered search spam. Increasing prominence http://servis-racunara.zzl.org/ A variety of methods can increase the prominence of a webpage within the search results. Cross linking between pages of the same website to provide more links to most important pages may improve its visibility. Writing content that includes frequently searched keyword phrase, so as to be relevant to a wide variety of search queries will tend to increase traffic. Updating content so as to keep search engines crawling back frequently can give additional weight to a site. Adding relevant keywords to a web page's meta data, including the title tag and meta description, will tend to improve the relevancy of a site's search listings, thus increasing traffic. URL normalization of web pages accessible via multiple urls, using the "canonical" meta tag or via 301 redirects can help make sure links to different versions of the url all count towards the page's link popularity score. White hat versus black hat techniques http://servis-racunara.zzl.org/ SEO techniques can be classified into two broad categories: techniques that search engines recommend as part of good design, and those techniques of which search engines do not approve. The search engines attempt to minimize the effect of the latter, among them spamdexing. Industry commentators have classified these methods, and the practitioners who employ them, as either white hat SEO, or black hat SEO. White hats tend to produce results that last a long time, whereas black hats anticipate that their sites may eventually be banned either temporarily or permanently once the search engines discover what they are doing. An SEO technique is considered white hat if it conforms to the search engines' guidelines and involves no deception. As the search engine guidelines are not written as a series of rules or commandments, this is an important distinction to note. White hat SEO is not just about following guidelines, but is about ensuring that the content a search engine indexes and subsequently ranks is the same content a user will see. White hat advice is generally summed up as creating content for users, not for search engines, and then making that content easily accessible to the spiders, rather than attempting to trick the algorithm from its intended purpose. White hat SEO is in many ways similar to web development that promotes accessibility,although the two are not identical. Black hat SEO attempts to improve rankings in ways that are disapproved of by the search engines, or involve deception. One black hat technique uses text that is hidden, either as text colored similar to the background, in an invisible div, or positioned off screen. Another method gives a different page depending on whether the page is being requested by a human visitor or a search engine, a technique known as cloaking. Search engines may penalize sites they discover using black hat methods, either by reducing their rankings or eliminating their listings from their databases altogether. Such penalties can be applied either automatically by the search engines' algorithms, or by a manual site review. One example was the February 2006 Google removal of both BMW and Ricoh for use of deceptive practices. Both companies, however, quickly apologized, fixed the offending pages, and were restored to Google's list. As a marketing strategy SEO is not an appropriate strategy for every website, and other Internet marketing strategies can be more effective, depending on the site operator's goals.A successful Internet marketing campaign may also depend upon building high quality web pages to engage and persuade, setting up analytics programs to enable site owners to measure results, and improving a site's conversion rate. http://ciscenje-laptopa-novi-sad.eu.pn/ SEO may generate an adequate return on investment. However, search engines are not paid for organic search traffic, their algorithms change, and there are no guarantees of continued referrals. Due to this lack of guarantees and certainty, a business that relies heavily on search engine traffic can suffer major losses if the search engines stop sending visitors. Search engines can change their algorithms, impacting a website's placement, possibly resulting in a serious loss of traffic. According to Google's CEO, Eric Schmidt, in 2010, Google made over 500 algorithm changes - almost 1.5 per day. It is considered wise business practice for website operators to liberate themselves from dependence on search engine traffic. Seomoz.org has suggested that "search marketers, in a twist of irony, receive a very small share of their traffic from search engines." Instead, their main sources of traffic are links from other websites. International markets http://ciscenje-laptopa-novi-sad.eu.pn Optimization techniques are highly tuned to the dominant search engines in the target market. The search engines' market shares vary from market to market, as does competition. In 2003, Danny Sullivan stated that Google represented about 75% of all searches. In markets outside the United States, Google's share is often larger, and Google remains the dominant search engine worldwide as of 2007. As of 2006, Google had an 85-90% market share in Germany.While there were hundreds of SEO firms in the US at that time, there were only about five in Germany. As of June 2008, the marketshare of Google in the UK was close to 90% according to Hitwise. That market share is achieved in a number of countries. As of 2009, there are only a few large markets where Google is not the leading search engine. In most cases, when Google is not leading in a given market, it is lagging behind a local player. The most notable markets where this is the case are China, Japan, South Korea, Russia and the Czech Republic where respectively Baidu, Yahoo! Japan, Naver, Yandex and Seznam are market leaders. http://inputns.webs.com/ Successful search optimization for international markets may require professional translation of web pages, registration of a domain name with a top level domain in the target market, and web hosting that provides a local IP address. Otherwise, the fundamental elements of search optimization are essentially the same, regardless of language. www.ciscenje-laptopa-novi-sad.eu.pn
 
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