We propose the Critical Sentence Vector Model (CSVM), a novel model to measure text similarity. The CSVM accounts for the structural and semantic information of the document. Compared to existing methods based on keyword vector, e.g. Vector Space Model (VSM), CSVM measures documents similarity by measuring similarity between critical sentence vectors extracted from documents. Experiments show that CSVM outperforms VSM in calculation of text similarity.
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||2nd Asia Information Retrieval Symposium, AIRS 2005|
|Country||Korea, Republic of|
|Period||13/10/05 → 15/10/05|
- Theoretical Computer Science
- Computer Science(all)