Finding readings for scientists from social websites.

Current search systems are designed to find relevant articles, especially topically relevant ones, but the notion of relevance largely depends on search tasks. We study the specific task that scientists are searching for worth-reading articles beneficial for their research. Our study finds: users' perception of relevance and preference of reading are only moderately correlated; current systems can effectively find readings that are highly relevant to the topic, but 36% of the worth-reading articles are only marginally relevant or even non-relevant. Our system can effectively find those worth-reading but marginally relevant or non-relevant articles by taking advantages of scientists' recommendations in social websites.