  Automatic summarization of legal case documents is an important and practical
challenge. Apart from many domain-independent text summarization algorithms
that can be used for this purpose, several algorithms have been developed
specifically for summarizing legal case documents. However, most of the
existing algorithms do not systematically incorporate domain knowledge that
specifies what information should ideally be present in a legal case document
summary. To address this gap, we propose an unsupervised summarization
algorithm DELSumm which is designed to systematically incorporate guidelines
from legal experts into an optimization setup. We conduct detailed experiments
over case documents from the Indian Supreme Court. The experiments show that
our proposed unsupervised method outperforms several strong baselines in terms
of ROUGE scores, including both general summarization algorithms and
legal-specific ones. In fact, though our proposed algorithm is unsupervised, it
outperforms several supervised summarization models that are trained over
thousands of document-summary pairs.
