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There is an abundance of duplicated web documents on the internet. For example, two documents online could be very similar to each other except for a very small portion, such as URLs and advertisements. While such differences are not important with regards to web searches, they do tamper with web search results due to duplication. Therefore, if web crawlers could check the duplication percentage of newly crawled pages by a previously crawled page, the quality of web search will significantly increase. The main objective of this research is to propose a method which is able to check the duplication ratio of the content on the page with the one already crawled previously. The solution includes running a web crawling algorithm in order to calculate the ratio of duplication at the time of web crawling. In order to effectively achieve the goals of this research, Charikar’s SIMHASH finger printing-technique has been used. Using this, a new technique for the purpose of detection of exact and near duplication method will be devised which will work to check the duplication ratio with the newly crawled page. The experiment is carried out on multiple pages of two major B2B website namely Ali Baba and Trade key. More than 300 pages from two similar categories on each portal were selected for this experiment. These selected pages were first calculated using a third party duplication detection tool to set the bench mark. The results obtained from the test looked to be very promising and close to the benchmark set. The system running time was very short. However, the results show an average curve variation of 10% away from the bench mark which in this case is fine. Based on the results obtained from the experiment carried out, it can be said that Charikar’s SIMHASH finger printing technique can be effectively used to detect duplication and near duplication. In today’s world of technology, everything is easily accessible on the internet in the form of data. This data is available in the form of “content”; which, with the passage of time, has grown massively. It is almost impossible to find the desired content from such a large amount of data available. This is where search engines play a vital role in finding the desired data from the trillions of megabytes available. Web crawling is useful during such situations. Web crawlers play a vital role in the helping search engines find results. There are mainly two types of web crawlers, the Generic WebCrawler [1] and Focused WebCrawler [2]. The Generic WebCrawler focuses on all the generic content available on the web. Slightly less powerful in comparison, their function is to capture content generally available on the web. Focused Web crawlers; however, are special web crawlers whose main job is to search for relevant and specific content. These particular crawlers use specially created logic/knowledge to limit the crawling to limited pages, offering specific domains of content. Thus, Focused crawlers mainly look for specific topics already defined and decided. Documents that are exact clones of other documents are easy to identify and detect. Any conventional hash mechanism like MD5 (Message-Digest) [3] and SHA (Secure Hash Algorithm) [4] can effectively detect another document with 100% duplication. However, when it comes to detecting documents with near-duplication, things get more difficult. Near duplicate content on the web is much more challenging. With regards to content, in any two given pages, everything can be same except for a small portion that differs such as featured advertisements. Even though the content and other section of the page remains the same on every refresh, the advertisement URL keeps changing. Due to this small change, the entire page is categorized by crawlers as different each time. Similarly, counters and time stamp may also make the page different at every crawl.

Detection Of Duplicate And Near-Duplicate Content For Web Crawlers