Association for Computing Machinery
A high quality hierarchical organization of the concepts in a dataset at different levels of granularity has many valuable applications such as search, summarization, and con-tent browsing. In this paper, the authors propose an algorithm for recursively constructing a hierarchy of topics from a collection of content-representative documents. They characterize each topic in the hierarchy by an integrated ranked list of mixed-length phrases. Their mining framework is based on a phrase-centric view for clustering, extracting, and ranking topical phrases.