Research of Ranking Algorithm Based on Information Quantity and Entropy in Meta Search Engine
Shengli Wu · 2012
The meta search engine collects results from many search engines,using a certain way to treat the results and then returning back to the users.Reranking the results will directly affect the performance of meta search engine.This paper was based on information quantity and entropy which are used in communication field then presented a calculation algorithm——information related degree(IRD),after a particular amendment to the IRD algorithm,this paper also proposed a merging algorithm combMul.The above algorithms were applied to the meta search engine,and MRR precision was used to evaluate the algorithm.The MRR precision data show that IRD algorithm is even better compared with a widely used sorting algorithm——Borda.