TY - GEN
T1 - Link analysis for representing and retrieving legal information
AU - López Monroy, Alfredo
AU - Calvo, Hiram
AU - Gelbukh, Alexander
AU - García Pacheco, Georgina
N1 - Funding Information:
Work done under partial support of the Mexican Government (CONACyT, SNI), PIFI and SIP-IPN, Mexico, and RITOS-2. We thank Conacyt for the grant 205897 and project funding 60557.
PY - 2013
Y1 - 2013
N2 - Legal texts consist of a great variety of texts, for example laws, rules, statutes, etc. This kind of documents has as an important feature, that they are strongly linked among them, since they include references from one part to another. This makes it difficult to consult them, because in order to satisfy an information request, it is necessary to gather several references and rulings from a single text, and even with other texts. The goal of this work is to help in the process of consulting legal rulings through their retrieval from a request expressed as a question in natural language. For this, a formal model is proposed; this model is based on a weighted, non-directed graph; nodes represent the articles that integrate each document, and its edges represent references between articles and their degree of similarity. Given a question, this is added to the graph, and by combining a shortest-path algorithm with edge weight analysis, a ranked list of articles is obtained. To evaluate the performance of the proposed model we gathered 8,987 rulings and evaluated the answer to 40 test-questions as correct, incorrect or partial. A lawyer validated the answer to these questions. We compared results with other systems such as Lucene and JIRS (Java Information Retrieval System).
AB - Legal texts consist of a great variety of texts, for example laws, rules, statutes, etc. This kind of documents has as an important feature, that they are strongly linked among them, since they include references from one part to another. This makes it difficult to consult them, because in order to satisfy an information request, it is necessary to gather several references and rulings from a single text, and even with other texts. The goal of this work is to help in the process of consulting legal rulings through their retrieval from a request expressed as a question in natural language. For this, a formal model is proposed; this model is based on a weighted, non-directed graph; nodes represent the articles that integrate each document, and its edges represent references between articles and their degree of similarity. Given a question, this is added to the graph, and by combining a shortest-path algorithm with edge weight analysis, a ranked list of articles is obtained. To evaluate the performance of the proposed model we gathered 8,987 rulings and evaluated the answer to 40 test-questions as correct, incorrect or partial. A lawyer validated the answer to these questions. We compared results with other systems such as Lucene and JIRS (Java Information Retrieval System).
UR - http://www.scopus.com/inward/record.url?scp=84875549245&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-37256-8_32
DO - 10.1007/978-3-642-37256-8_32
M3 - Contribución a la conferencia
SN - 9783642372551
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 380
EP - 393
BT - Computational Linguistics and Intelligent Text Processing - 14th International Conference, CICLing 2013, Proceedings
T2 - 14th Annual Conference on Intelligent Text Processing and Computational Linguistics, CICLing 2013
Y2 - 24 March 2013 through 30 March 2013
ER -