Hier-SPCNet: A Legal Statute Hierarchy-based Heterogeneous Network for Computing Legal Case Document Similarity
This work addresses a domain-specific challenge in Legal IR by improving document similarity for legal professionals, though it is incremental as it builds on existing network-based approaches.
The authors tackled the problem of computing similarity between legal case documents by augmenting the existing precedent citation network with a hierarchy of legal statutes, forming a heterogeneous network called Hier-SPCNet. Experiments on Indian Supreme Court case documents showed significantly better similarity estimation compared to prior network-based methods.
Computing similarity between two legal case documents is an important and challenging task in Legal IR, for which text-based and network-based measures have been proposed in literature. All prior network-based similarity methods considered a precedent citation network among case documents only (PCNet). However, this approach misses an important source of legal knowledge -- the hierarchy of legal statutes that are applicable in a given legal jurisdiction (e.g., country). We propose to augment the PCNet with the hierarchy of legal statutes, to form a heterogeneous network Hier-SPCNet, having citation links between case documents and statutes, as well as citation and hierarchy links among the statutes. Experiments over a set of Indian Supreme Court case documents show that our proposed heterogeneous network enables significantly better document similarity estimation, as compared to existing approaches using PCNet. We also show that the proposed network-based method can complement text-based measures for better estimation of legal document similarity.