We present a new L1-distance-based k-means clustering algorithm to address the challenge of clustering high-dimensional proportional vectors. The new algorithm explicitly incorpor...
Bonnie K. Ray, Hisashi Kashima, Jianying Hu, Monin...
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Multi-Feature Index Tree (MFI-Tree), a new indexing structure, is proposed to index multiple high-dimensional features of video data for video retrieval through example. MFI-Tree e...
Searching for people on the Web is one of the most common query types to the web search engines today. However, when a person name is queried, the returned webpages often contain ...
Dmitri V. Kalashnikov, Rabia Nuray-Turan, Sharad M...
Search engine logs are an emerging new type of data that offers interesting opportunities for data mining. Existing work on mining such data has mostly attempted to discover knowl...