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  • The Benefits of Using Ongoing Search Engine Optimization Services

    Many new clients of search engine optimization companies are unsure if they should opt for one-time search engine optimization services or ongoing services. One-time SEO services are appropriate for new websites for several reasons. Once you do the initial optimization of a new website, you have to wait a while in order to receive data that will help you determine the direction in which you need to optimize the site. A period of six months or so will give you enough data to determine what will and won't work for the site.

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  • SEO Optimization Services - Finding the Best Guide

    What should you look for in a company that offers SEO optimization services? It is an all-important question that you need to answer when choosing a service provider for all your SEO optimization requirements. As you read on, you will find out three key qualities that you need to look for when choosing an SEO optimization service that is a perfect fit for you.

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  • The 7 Pillars of Search Engine Optimization and Marketing

    Search engine optimization (SEO) is all about bringing your website to the 1st page of every major search engine. However, the ultimate goals of SEO services are to increase targeted traffic to your website, improve convergence and increase sales. A successful search engine optimization strategy must involve all possible elements which fit a specific website. It must include the 7 pillars of search engine optimization.

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  • The Backbone of SEO - On Page Optimization

    Do you want to know my dears the backbone of SEO? Well this is called as On Page Optimization which includes a variety of factors such as Meta tags optimization, key word density, image optimization, site navigation, and sitemaps. Today it has made its worth renowned due to its dynamic and versatile nature over the World Wide Web.

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  • SEO - Off-Page Optimization in Detail

    You would think that after you lock in your on-page optimization efforts, that you were half done, right? Wrong, although on-page optimization is one of only two categories, off-page optimization takes times, patience, and not to mention, it's never ending.

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  • SEO - On-Page Optimization in Detail

    As I've mentioned in a previous article, SEO can be broken down into two categories, on-page optimization and off-page optimization. In this article however, I'm only going to focus on on-page optimization.

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  • How to Associate Web Design With Search Engine Optimization

    Permanent one way link building is an important means of search engine optimization as the basic idea behind optimization is to establish link popularity. Meta tag optimization has also given adequate boost to many companies although this technique cannot be adopted by novices and requires the guidance of an established SEO firm. SEO is a huge business and one of the most offered service packages on the World Wide Web.

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  • Search Engine Optimization - 3 Tips For Building Quality Backlinks

    When most people think of Search Engine Optimization (SEO), they usually concentrate solely on keyword optimization. While keyword optimization is very important, it is not the only thing that will make your website or blog search engine friendly. There are other factors that can greatly determine the effectiveness of your site. One of those factors that we'll be discussing today is inbound links, otherwise known as back links.

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  • Search Optimization Company - The Great Visibility Over Internet

    A professional search optimization company helps businesses to benefit in huge with their research, planning and marketing services. Irrespective of the business size, these companies are the great help for the websites in offering them excellent online visibility. The website optimization experts at the search optimization company deliver a number of striking and innovative solutions for the businesses.

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  • The Lasting Future of Search Engine Optimization

    The search engine optimization has surely a long lasting future these days. The worth of organic SEO has been increased due to its exclusive techniques involving On Page Optimization and Off Page Optimization. That is why you could find most of the lucrative SEO jobs on the internet nowadays.

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  • 5 Strategic Reasons For Website Optimization

    Website optimization, also known as search engine optimization (SEO) helps your loyal customers discover your other products and services online, quicker and with much less effort. Moreover, website optimization is a proven way to find new customers who are right now searching for your type of products or services.

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  • How to Associate Web Design With Search Engine Optimization

    Permanent one way link building is an important means of search engine optimization as the basic idea behind optimization is to establish link popularity. Meta tag optimization has also given adequate boost to many companies although this technique cannot be adopted by novices and requires the guidance of an established SEO firm. SEO is a huge business and one of the most offered service packages on the World Wide Web.

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  • How to get star query optimization in SQL Server 2005

    - by Jan
    I have a star schema but SQL Server 2005 always uses the clustered indexes to access a table. What parameters do I have to set to enable this optimization. According to http://blogs.msdn.com/sqlqueryprocessing/archive/2007/04/09/how-to-check-whether-the-final-query-plan-is-optimized-for-star-join.aspx and the DWH datasheet of SQL Server 2005 both claim, that SQL Server 2005 support this feature.

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  • Free Optimization Library in C#

    - by Ngu Soon Hui
    Is there any optimization library in C#? I have to optimize a complicated equation in excel, for this equation there are a few coefficients. And I have to optimize them according to a fitness function that I define. So I wonder whether there is such a library that does what I need?

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  • Performance Optimization for Matrix Rotation

    - by Summer_More_More_Tea
    Hello everyone: I'm now trapped by a performance optimization lab in the book "Computer System from a Programmer's Perspective" described as following: In a N*N matrix M, where N is multiple of 32, the rotate operation can be represented as: Transpose: interchange elements M(i,j) and M(j,i) Exchange rows: Row i is exchanged with row N-1-i A example for matrix rotation(N is 3 instead of 32 for simplicity): ------- ------- |1|2|3| |3|6|9| ------- ------- |4|5|6| after rotate is |2|5|8| ------- ------- |7|8|9| |1|4|7| ------- ------- A naive implementation is: #define RIDX(i,j,n) ((i)*(n)+(j)) void naive_rotate(int dim, pixel *src, pixel *dst) { int i, j; for (i = 0; i < dim; i++) for (j = 0; j < dim; j++) dst[RIDX(dim-1-j, i, dim)] = src[RIDX(i, j, dim)]; } I come up with an idea by inner-loop-unroll. The result is: Code Version Speed Up original 1x unrolled by 2 1.33x unrolled by 4 1.33x unrolled by 8 1.55x unrolled by 16 1.67x unrolled by 32 1.61x I also get a code snippet from pastebin.com that seems can solve this problem: void rotate(int dim, pixel *src, pixel *dst) { int stride = 32; int count = dim >> 5; src += dim - 1; int a1 = count; do { int a2 = dim; do { int a3 = stride; do { *dst++ = *src; src += dim; } while(--a3); src -= dim * stride + 1; dst += dim - stride; } while(--a2); src += dim * (stride + 1); dst -= dim * dim - stride; } while(--a1); } After carefully read the code, I think main idea of this solution is treat 32 rows as a data zone, and perform the rotating operation respectively. Speed up of this version is 1.85x, overwhelming all the loop-unroll version. Here are the questions: In the inner-loop-unroll version, why does increment slow down if the unrolling factor increase, especially change the unrolling factor from 8 to 16, which does not effect the same when switch from 4 to 8? Does the result have some relationship with depth of the CPU pipeline? If the answer is yes, could the degrade of increment reflect pipeline length? What is the probable reason for the optimization of data-zone version? It seems that there is no too much essential difference from the original naive version. EDIT: My test environment is Intel Centrino Duo processor and the verion of gcc is 4.4 Any advice will be highly appreciated! Kind regards!

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  • Need help with basic optimization problem

    - by ??iu
    I know little of optimization problems, so hopefully this will be didactic for me: rotors = [1, 2, 3, 4...] widgets = ['a', 'b', 'c', 'd' ...] assert len(rotors) == len(widgets) part_values = [ (1, 'a', 34), (1, 'b', 26), (1, 'c', 11), (1, 'd', 8), (2, 'a', 5), (2, 'b', 17), .... ] Given a fixed number of widgets and a fixed number of rotors, how can you get a series of widget-rotor pairs that maximizes the total value where each widget and rotor can only be used once?

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  • C++ Performance/memory optimization guidelines

    - by ML
    Hi All, Does anyone have a resource for C++ memory optimization guidelines? Best practices, tuning, etc? As an example: Class xxx { public: xxx(); virtual ~xxx(); protected: private: }; Would there be ANY benefit on the compiler or memory allocation to get rid of protected and private since there there are no items that are protected and private in this class?

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  • Any Javascript optimization benchmarks?

    - by int3
    I watched Nicholas Zakas' talk, Speed up your Javascript, with some interest. I liked how he benchmarked the various performance improvements created by various optimization techniques, e.g. reducing calls to deeply nested objects, changing loops to count down instead of up, etc. I would like to run these benchmarks myself though, to see exactly how our current browsers are faring. I guess it wouldn't be too difficult to cook up some timed loops, but I'd like to know if there are any existing implementations out there.

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  • Java code optimization leads to numerical inaccuracies and errors

    - by rano
    I'm trying to implement a version of the Fuzzy C-Means algorithm in Java and I'm trying to do some optimization by computing just once everything that can be computed just once. This is an iterative algorithm and regarding the updating of a matrix, the clusters x pixels membership matrix U, this is the update rule I want to optimize: where the x are the element of a matrix X (pixels x features) and v belongs to the matrix V (clusters x features). And m is a parameter that ranges from 1.1 to infinity. The distance used is the euclidean norm. If I had to implement this formula in a banal way I'd do: for(int i = 0; i < X.length; i++) { int count = 0; for(int j = 0; j < V.length; j++) { double num = D[i][j]; double sumTerms = 0; for(int k = 0; k < V.length; k++) { double thisDistance = D[i][k]; sumTerms += Math.pow(num / thisDistance, (1.0 / (m - 1.0))); } U[i][j] = (float) (1f / sumTerms); } } In this way some optimization is already done, I precomputed all the possible squared distances between X and V and stored them in a matrix D but that is not enough, since I'm cycling througn the elements of V two times resulting in two nested loops. Looking at the formula the numerator of the fraction is independent of the sum so I can compute numerator and denominator independently and the denominator can be computed just once for each pixel. So I came to a solution like this: int nClusters = V.length; double exp = (1.0 / (m - 1.0)); for(int i = 0; i < X.length; i++) { int count = 0; for(int j = 0; j < nClusters; j++) { double distance = D[i][j]; double denominator = D[i][nClusters]; double numerator = Math.pow(distance, exp); U[i][j] = (float) (1f / (numerator * denominator)); } } Where I precomputed the denominator into an additional column of the matrix D while I was computing the distances: for (int i = 0; i < X.length; i++) { for (int j = 0; j < V.length; j++) { double sum = 0; for (int k = 0; k < nDims; k++) { final double d = X[i][k] - V[j][k]; sum += d * d; } D[i][j] = sum; D[i][B.length] += Math.pow(1 / D[i][j], exp); } } By doing so I encounter numerical differences between the 'banal' computation and the second one that leads to different numerical value in U (not in the first iterates but soon enough). I guess that the problem is that exponentiate very small numbers to high values (the elements of U can range from 0.0 to 1.0 and exp , for m = 1.1, is 10) leads to ver y small values, whereas by dividing the numerator and the denominator and THEN exponentiating the result seems to be better numerically. The problem is it involves much more operations. Am I doing something wrong? Is there a possible solution to get both the code optimized and numerically stable? Any suggestion or criticism will be appreciated.

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  • PHP website Optimization

    - by ana
    I have a high traffic website and I need make sure my site is fast enough to display my pages to everyone rapidly. I searched on Google many articles about speed and optimization and here's what I found: Cache the page Save it to the disk Caching the page in memory: This is very fast but if I need to change the content of my page I have to remove it from cache and then re-save the file on the disk. Save it to disk This is very easy to maintain but every time the page is accessed I have to read on the disk. Which method should I go with? Thanks

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  • Performance optimization strategies of last resort?

    - by jerryjvl
    There are plenty of performance questions on this site already, but it occurs to me that almost all are very problem-specific and fairly narrow. And almost all repeat the advice to avoid premature optimization. Let's assume: the code already is working correctly the algorithms chosen are already optimal for the circumstances of the problem the code has been measured, and the offending routines have been isolated all attempts to optimize will also be measured to ensure they do not make matters worse What I am looking for here is strategies and tricks to squeeze out up to the last few percent in a critical algorithm when there is nothing else left to do but whatever it takes. Ideally, try to make answers language agnostic, and indicate any down-sides to the suggested strategies where applicable. I'll add a reply with my own initial suggestions, and look forward to whatever else the SO community can think of.

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  • Does MATLAB perform tail call optimization?

    - by Shea Levy
    I've recently learned Haskell, and am trying to carry the pure functional style over to my other code when possible. An important aspect of this is treating all variables as immutable, i.e. constants. In order to do so, many computations that would be implemented using loops in an imperative style have to be performed using recursion, which typically incurs a memory penalty due to the allocation a new stack frame for each function call. In the special case of a tail call (where the return value of a called function is immediately returned to the callee's caller), however, this penalty can be bypassed by a process called tail call optimization (in one method, this can be done by essentially replacing a call with a jmp after setting up the stack properly). Does MATLAB perform TCO by default, or is there a way to tell it to?

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