It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
In most IR clustering problems, we directly cluster the documents, working in the document space, using cosine similarity between documents as the similarity measure. In many real...
Multi-document summarization aims to create a compressed summary while retaining the main characteristics of the original set of documents. Many approaches use statistics and mach...
Dingding Wang, Tao Li, Shenghuo Zhu, Chris H. Q. D...
Background: Clustering is a key step in the analysis of gene expression data, and in fact, many classical clustering algorithms are used, or more innovative ones have been designe...
With the availability of affordable sensors and sensor networks, sensor-based human-activity recognition has attracted much attention in artificial intelligence and ubiquitous comp...