Today, search engine is the most commonly used tool for Web information retrieval, however, its current status is still far from satisfaction. This paper focuses on clustering Web search results in order to help users find relevant Web information more easily and quickly. The main contributions of this paper include the following. (1) The benefits of using key phrases as natural language information features are discussed. An effective and efficient algorithm based on suffix array for key phrase discovery is presented. The efficiency of this method is very high no matter how large the language's alphabet is. (2) The concept of orthogonal clustering is proposed for general clustering problems. The reason why matrix SVD (Singular Value Decomposition) can provide solution to orthogonal clustering is strictly proved. The orthogonal clustering algorithm has a solid mathematics foundation and many advantages over traditional heuristic clustering algorithms. (3) The WICE system is designed and implemented to automatically organize multilingual Web search results through a semantic, hierarchical, online clustering approach named SHOC.
Later in 2001, the SHOC (Semantic, Hierarchical, Online Clustering) algorithm was introduced REF .
Semantic, Hierarchical, Online Clustering of Web Search Results
APWeb
Computer Science