Optimization Curl Crawler: A Framework for Crawling the Web with Page Ranking Optimization Platform

WWW is now the exposed and up-to-date huge repository of information available to everyone, everywhere and every time [1]. It is the thrust arena of engineering endeavor and is evolving without a grand design blueprint. WWW is immense to obtain information and moreover information on web is voyaged using search engines like AltaVista, WebCrawler, Hot Boat etc [1,4]. Owing to the reason that search engines are the striking one to sail the web for several purposes. This paper is an experimental strives to develop and implement a framework with extended architecture to make search engines more efficient using local resource utilization features of the programming. This paper presents the concept of page ranking optimization to optimize ranking of result by information retrieval module of search engines with hybrid approach of logic for searching. This is an implementation experience for use of local optimization to provide user friendly search engine marketing platform (i.e. Internet marketing) with focused and path oriented approach for cross featured. In addition to curl programming, personalization of information, caching and graphical perception, main features of this framework are cross platform, cross architecture, focused, path oriented, human powered and ranking optimization. The first part of the paper covers related work that has been done mostly in the field of general search engine in over ongoing research project for crawling and ranking the web pages. The second part defines architecture and functioning of developed framework and compares it to search engine optimization for web pages. The third part provides an overview and critical analysis of developed framework like experimental results, pseudo code, data structure etc.