We present a divide-and-merge methodology for clustering a set of objects that combines a top-down "divide" phase with a bottom-up "merge" phase. In contrast, ...
David Cheng, Santosh Vempala, Ravi Kannan, Grant W...
We consider the problem of retrieving multiple documents relevant to the single subtopics of a given web query, termed “full-subtopic retrieval”. To solve this problem we pres...
Andrea Bernardini, Claudio Carpineto, Massimiliano...
This paper compares the efficacy and efficiency of different clustering approaches for selecting a set of exemplar images, to present in the context of a semantic concept. We eval...
This paper presents a new probabilistic framework of Mandarin speech recognition by incorporating a sophisticated hierarchical prosody model into the conventional HMM-based system...
Broad-coverage lexical resources such as WordNet are extremely useful. However, they often include many rare senses while missing domain-specific senses. We present a clustering a...