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....
We consider a network of autonomous peers forming a logically global but physically distributed search engine, where every peer has its own local collection generated by independe...
Josiane Xavier Parreira, Sebastian Michel, Gerhard...
In dynamic environments with frequent content updates, we require online full-text search that scales to large data collections and achieves low search latency. Several recent met...
In automated text categorization, given a small number of labeled documents, it is very challenging, if not impossible, to build a reliable classifier that is able to achieve high...
Zenglin Xu, Rong Jin, Kaizhu Huang, Michael R. Lyu...
Retrieving relevant information in Data and Knowledge Bases containing a large number of di erent types of information is a non trivial problem. That is the reason why, in areas l...