Is Google really the best search engine?

Yes

1 of 5

by Michelle Lea

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Ok, in my book, Google rocks! I personally have tried Yahoo, MSN and other search engines, but Google finds exactly what I need when the others sometimes don't. I've found Google to be faster, more efficient with better search results.

After doing some extensive research about Google, I've discovered alot more of what all they have to offer! Contributing Source http://www.google.co m/coop/cse/ Did you know that you can have a custom search engine with Google? You can use the power of Google to create a search engine tailored to fit your needs. Like include one website, multiple websites, or specific webpages, host the search box and results on your own website and customize the colors and branding to match your existing webpages. Custom search can benefit your website, blog or special interest group by helping your visitors find what they are looking for, you can invite your friends and community to contribute, make money with AdSense for Search, and automatically generate a search engine based on the links on your website or blogroll with Custom Search on the fly . Your business or enterprise can take full advantage of Google Site Search for added benefits, like enterprise-grade support, ads-free results pages, and the XML API, put your own logo on the search results pages, you can even help customers navigate your site and find the products they wish to buy. Your non-profit, government, or educational organization can show search results without ads.

The following are some highlights about Google that I found very interesting at the following contributing source: http://infolab.stanf ord.edu/~backrub/goo gle.html "The Anatomy of a Large-Scale Hypertextual Web Search Engine"; "In this paper, we present Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext. Google is designed to crawl and index the Web efficiently and produce much more satisfying search results than existing systems. The prototype with a full text and hyperlink database of at least 24 million pages is available at http://google.stanfo rd.edu/ To engineer a search engine is a challenging task. Search engines index tens to hundreds of millions of web pages involving a comparable number of distinct terms. They answer tens of millions of queries every day. Despite the importance of large-scale search engines on the web, very little academic research has been done on them. Furthermore, due to rapid advance in technology and web proliferation, creating a web search engine today is very different from three years ago. This paper provides an in-depth description of our large-scale web search engine - the first such detailed public description we know of to date. Apart from the problems of scaling traditional search techniques to data of this magnitude, there are new technical challenges involved with using the additional information present in hypertext to produce better search results. This paper addresses this question of how to build a practical large-scale system which can exploit the additional information present in hypertext. Also we look at the problem of how to effectively deal with uncontrolled hypertext collections where anyone can publish anything they want. (Keywords: World Wide Web, Search Engines, Information Retrieval, PageRank, Google) We have built a large-scale search engine which addresses many of the problems of existing systems. It makes especially heavy use of the additional structure present in hypertext to provide much higher quality search results. We chose our system name, Google, because it is a common spelling of googol, or 10100 and fits well with our goal of building very large-scale search engines. Creating a search engine which scales even to today's web presents many challenges. Fast crawling technology is needed to gather the web documents and keep them up to date. Storage space must be used efficiently to store indices and, optionally, the documents themselves. The indexing system must process hundreds of gigabytes of data efficiently. Queries must be handled quickly, at a rate of hundreds to thousands per second. These tasks are becoming increasingly difficult as the Web grows. However, hardware performance and cost have improved dramatically to partially offset the difficulty. There are, however, several notable exceptions to this progress such as disk seek time and operating system robustness. In designing Google, we have considered both the rate of growth of the Web and technological changes. Google is designed to scale well to extremely large data sets. It makes efficient use of storage space to store the index. Its data structures are optimized for fast and efficient access (see section 4.2. Further, we expect that the cost to index and store text or HTML will eventually decline relative to the amount that will be available (see Appendix B. This will result in favorable scaling properties for centralized systems like Google. Our main goal is to improve the quality of web search engines. There is quite a bit of recent optimism that the use of more hypertextual information can help improve search and other applications [Marchiori 97 [Spertus 97 [Weiss 96 [Kleinberg 98. In particular, link structure [Page 98 and link text provide a lot of information for making relevance judgments and quality filtering. Google makes use of both link structure and anchor text (see Sections 2.1 and 2.2. Our final design goal was to build an architecture that can support novel research activities on large-scale web data. To support novel research uses, Google stores all of the actual documents it crawls in compressed form. One of our main goals in designing Google was to set up an environment where other researchers can come in quickly, process large chunks of the web, and produce interesting results that would have been very difficult to produce otherwise. In the short time the system has been up, there have already been several papers using databases generated by Google, and many others are underway. Another goal we have is to set up a Spacelab-like environment where researchers or even students can propose and do interesting experiments on our large-scale web data. The Google search engine has two important features that help it produce high precision results. First, it makes use of the link structure of the Web to calculate a quality ranking for each web page. This ranking is called PageRank and is described in detail in [Page 98]. Second, Google utilizes link to improve search results. PageRank prioritizes the results (demo available at google.stanford.edu. Aside from PageRank and the use of anchor text, Google has several other features. First, it has location information for all hits and so it makes extensive use of proximity in search. Second, Google keeps track of some visual presentation details such as font size of words. Words in a larger or bolder font are weighted higher than other words. Third, full raw HTML of pages is available in a repository. Running a web crawler is a challenging task. There are tricky performance and reliability issues and even more importantly, there are social issues. Crawling is the most fragile application since it involves interacting with hundreds of thousands of web servers and various name servers which are all beyond the control of the system. In order to scale to hundreds of millions of web pages, Google has a fast distributed crawling system. A single URLserver serves lists of URLs to a number of crawlers (we typically ran about 3). Both the URLserver and the crawlers are implemented in Python. Each crawler keeps roughly 300 connections open at once. This is necessary to retrieve web pages at a fast enough pace. At peak speeds, the system can crawl over 100 web pages per second using four crawlers. This amounts to roughly 600K per second of data. A major performance stress is DNS lookup. Each crawler maintains a its own DNS cache so it does not need to do a DNS lookup before crawling each document. Each of the hundreds of connections can be in a number of different states: looking up DNS, connecting to host, sending request, and receiving response. These factors make the crawler a complex component of the system. It uses asynchronous IO to manage events, and a number of queues to move page fetches from state to state. The most important measure of a search engine is the quality of its search results. While a complete user evaluation is beyond the scope of this paper, our own experience with Google has shown it to produce better results than the major commercial search engines for most searches."

The information you just read above, in my opinion, says it all and that was only highlights from that article! Please take time to visit the contributing source links above for a full article on Google, because once you've read all of the information/facts presented, I believe you'll have to agree with me that Google is tops when it comes to search engines! The articles prove that Google offers an overall better experience for all types of websufers.

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