| 摘要 |
Methods and systems are presented for recommending similar questions to one that a user has entered into a search engine. Previously-entered questions are subject to a clustering algorithm and placed into a hierarchy of clusters, with clusters set within clusters. For each cluster within the hierarchy, a representative vector, based on feature vectors of the items within the cluster, is calculated. A feature vector for the user's question is calculated and used, along with the representative vectors at each level in the hierarchy, to traverse and navigate the cluster hierarchy. When a leaf cluster is found, the items in the leaf cluster, such as the previously-entered questions are returned to the user. A subset of items in the leaf cluster, or items from other leaf clusters within a branch cluster, can be selected based on the number of items desired to be returned.
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