Waterloo at NTCIR-3: Using Self-supervised Word Segmentation
In this paper, we describe the system we use in the NTCIR-3 CLIR (cross language IR) task. We participate the SLIR (single language IR) track. In our system, we use a self-supervised word-segmentation technique for Chinese information retrieval, which combines the advantages of traditional dictionary based approaches with character based approaches, while overcoming many of their shortcomings. This method is completely language independent and unsupervised, which provides a promising avenue for constructing accurate multi-lingual or cross-lingual information retrieval systems that are flexible and adaptive.