In this paper we present PubSearch, a meta-search engine system for academic publications. We have designed a ranking algorithm consisting of a hierarchical set of heuristic models including term frequency, depreciated citation count and a graph-based score for associations among paper index terms. We used our algorithm to re-rank the default search results produced by online digital libraries such as ACM Portal in response to specific user-submitted queries. The experimental results show that the ranking algorithm used by our system can provide a more relevant ranking scheme compared to ACM Portal.