To be effective and useful, math search systems must not only maximize precision and recall, but also present the query hits in a form that makes it easy for the user to identify quickly the truly relevant hits. To meet that requirement, the search system must sort the hits according to domain-appropriate relevance criteria, and provide with each hit a query-relevant summary of the hit target. The standard relevance measures in text search, which rely mostly on keyword frequencies and document sizes, turned out to be inadequate in math search. Therefore, alternative relevance measures must be defined, which give more weight to certain types of information than to others and take into account cross-reference statistics. In this paper, new, multi-dimensional relevance metrics are defined for math search, methods for computing and implementing them are discussed, and comparative performance evaluation results are presented. Query-relevant hit-summary generation is another factor that ...