Ch19

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This document provides an overview of a web crawler case study that was implemented. The web crawler takes in a starting webpage, target string to search for, and limits the number of pages to 50. It uses graphs and hash tables to represent the web pages and links as it crawls. The algorithm adds the starting page to a hash set and graph, removes pages to search, checks for the target string, adds found links to the hash set and graph, and repeats until all pages are searched or the limit is reached.

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Introduces "Slug" a web crawler (or "Scutter") designed for harvesting semantic web content. Implemented in Java using the Jena API, Slug provides a configurable, modular framework that allows a great degree of flexibility in configuring the retrieval, processing and storage of harvested content. The framework provides an RDF vocabulary for describing crawler configurations and collects metadata concerning crawling activity. Crawler metadata allows for reporting and analysis of crawling progress, as well as more efficient retrieval through the storage of HTTP caching data.

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Abstract : The number of web pages is increasing into millions and trillions around the world. To make searching much easier for users, web search engines came into existence. Web Search engines are used to find specific information on the World Wide Web. Without search engines, it would be almost impossible to locate anything on the Web unless or until a specific URL address is known. This information is provided to search by a web crawler which is a computer program or software. Web crawler is an essential component of search engines, data mining and other Internet applications. Scheduling Web pages to be downloaded is an important aspect of crawling. Previous research on Web crawl focused on optimizing either crawl speed or quality of the Web pages downloaded. While both metrics are important, scheduling using one of them alone is insufficient and can bias or hurt overall crawl process. This paper is all about design a new Web Crawler using VB.NET Technology. Keywords: Web Crawler, Visual Basic Technology, Crawler Interface, Uniform Resource Locator.

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Ch19

1. Chapter 19 Web Crawler

7. FIGURE 19.1 User interface design

8. FIGURE 19.2 UML description

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Ch19