From Keywords to Context: How Focused Crawlers Improve Search Engine Accuracy

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Abstract

The accuracy of search engines relies heavily on the quality of data crawled from the web. Traditional crawlers face limitations due to their broad and unsystematic approach, often retrieving irrelevant content that dilutes the quality of search results. Focused crawlers, in contrast, optimize web crawling by narrowing the scope to specific topics or domains of interest, enhancing the precision and relevance of the collected data. This paper explores how focused crawlers improve search engine accuracy by leveraging keyword-based filtering, context-awareness, and relevance scoring techniques. By continuously refining their crawling strategies, focused crawlers ensure that only the most pertinent content is retrieved, contributing to more accurate search engine results. We discuss the methods, advantages, and challenges associated with focused crawling, and present case studies demonstrating its impact on search engine performance. Ultimately, this paper highlights the role of focused crawlers in shaping the future of more efficient, contextually aware web search.

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