This discussion is continuation of Tools and Technologies involved in modern search architecture . Please use the link to access the part-I for a quick recap as the topics mentioned there may be referred here. In Search implementation once you're done with the challenges of Crawling the content and building an Inverted Index to quickly access the matched documents two more challenges are up for you: Relevant results to the user - Relevance Score Deliver results to the user - SERP Relevance Score: Relevance scoring is used by search engines to identify the order in which the documents should appear. Here's a documented definition: Relevance scoring uses the Boolean model to find matching documents and a formula called the practical scoring function to calculate relevance. This formula borrows concepts from TF-IDF (term frequency/inverse document frequency) and the vector space model but adds more modern features like a coordination factor, field length no...
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