A Novel Relevance Metric Prediction Algorithm For a Personalized Web Search

Software metrics are the key performance indicators, using which the performance of a system can be assessed quantitatively. Metrics can also be applied for personalized web search which can be used to retrieve relevant results for each individual user depending on their unique profile. Although personalized search based on user profile has been under research for many years and various metrics have been proposed, it is still uncertain whether personalization is unswervingly effective on different queries for different user profiles. We present a framework for personalized search which retrieves result based on user profile and query type. Also we evaluate the performance of proposed system using relevance evaluation metrics.