Legal case document similarity: You need both network and text

Similarity Measures for Text Document Clustering

Clustering is a useful technique that organizes a large quantity of unordered text documents into a small number of meaningful and coherent clusters, thereby providing a basis for intuitive and informative navigation and browsing mechanisms. Partitional clustering algorithms have been recognized to be more suitable as opposed to the hierarchical clustering schemes for processing large datasets....

Automatic Term Extraction and Document Similarity in Special Text Corpora

This paper confirms that the performance of a state-of-the-art automatic term extraction method on a computer science corpus is similar to previously published performance data on a medical corpus. The extracted terms are then used to estimate the similarity of papers in the computer science corpus using the standard Vector Space Model. The precision of retrieval using a term-based representati...

A Text Similarity Approach for Precedence Retrieval from Legal Documents

Precedence retrieval of legal documents is an information retrieval task to retrieve prior case documents that are related to a given case document. This helps in automatic linking of related documents to ensure that identical situations are treated similarly in every case. Several methodologies, such as information extraction based on natural language processing, rule-based method, and machine...

Parametric or Direct Modeling: why you may need both

Vertical Bar Detection for Gauging Text Similarity of Document Images

A new method for gauging text similarity of image-based document using word shape recognition is proposed in this paper. Image features are directly extracted instead of using OCR (optical character recognition). The proposed method forms so-called vertical bar patterns by detecting local extrema points in word units extracted by segmenting the document images. These vertical bar patterns form ...