PUBSEARCH : A Hierarchical Heuristic Scheme for Ranking Academic Search Results
Publikation: Forskning - peer review › Konferenceartikel i proceeding
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.
|Titel||International Conference on Pattern Recognition Applications and Methods (ICPRAM 2012)|
|Udgivelsessted||Vilamoura, Algarve, Portugal|
|Konference||1st International Conference on Pattern Recognition Applications and Methods|
|Periode||06/02/12 → 08/02/12|