A variety of legal documents are increasingly being made available in electronic format. Automatic Information Search and Retrieval algorithms play a key role in enabling efficient access to such digitized documents. Although keyword-based search is the traditional method used for text retrieval, they perform poorly when literal term matching is done for query processing, due to synonymy and ambivalence of words. To overcome these drawbacks, an ontological framework to enhance the user’s query for retrieval of truly relevant legal judgments has (...) been proposed in this paper. Ontologies ensure efficient retrieval by enabling inferences based on domain knowledge, which is gathered during the construction of the knowledge base. Empirical results demonstrate that ontology-based searches generate significantly better results than traditional search methods. (shrink)

Legal judgments are complex in nature and hence a brief summary of the judgment, known as a headnote , is generated by experts to enable quick perusal. Headnote generation is a time consuming process and there have been attempts made at automating the process. The difficulty in interpreting such automatically generated summaries is that they are not coherent and do not convey the relative relevance of the various components of the judgment. A legal judgment can be segmented into coherent chunks (...) based on the rhetorical roles played by the sentences. In this paper, a comprehensive system is proposed for labeling sentences with their rhetorical roles and extracting structured head notes automatically from legal judgments. An annotated data set was created with the help of legal experts and used as training data. A machine learning technique, Conditional Random Field, is applied to perform document segmentation by identifying the rhetorical roles. The present work also describes the application of probabilistic models for the extraction of key sentences and composing the relevant chunks in the form of a headnote. The understanding of basic structures and distinct segments is shown to improve the final presentation of the summary. Moreover, by adding simple additional features the system can be extended to other legal sub-domains. The proposed system has been empirically evaluated and found to be highly effective on both the segmentation and summarization tasks. The final summary generated with underlying rhetorical roles improves the readability and efficiency of the system. (shrink)