  A previous similar case in common law systems can be used as a reference with
respect to the current case such that identical situations can be treated
similarly in every case. However, current approaches for judgment document
similarity computation failed to capture the core semantics of judgment
documents and therefore suffer from lower accuracy and higher computation
complexity. In this paper, a knowledge block summarization based machine
learning approach is proposed to compute the semantic similarity of Chinese
judgment documents. By utilizing domain ontologies for judgment documents, the
core semantics of Chinese judgment documents is summarized based on knowledge
blocks. Then the WMD algorithm is used to calculate the similarity between
knowledge blocks. At last, the related experiments were made to illustrate that
our approach is very effective and efficient in achieving higher accuracy and
faster computation speed in comparison with the traditional approaches.
