Information-retrieval Algorithm Based on Query Expansion and Classification
Yaping Lin · Jisuanji fangzhen · 2006
A new information retrieval algorithm based on query expansion and classification was proposed. The algorithm is based on the observation that very short queries used in information searching often result in depressed precision and impressive recall. The approach is based on pseudo-feedback and text classification, and it attempts to catch more relevant documents for user. The results of the experiment show that the algorithm proposed improves more precision and efficiency than the traditional query expansion methods.