Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...
We present a browser-extending Semantic Web extraction system that maps HTML documents to tables and, where possible, to rules. First, the basic data extractor ViPER distills and ...
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
Query expansion techniques generally select new query terms from a set of top ranked documents. Although a user’s manual judgment of those documents would much help to select goo...