Aspect Fusion as Design Paradigm for Legal Information Retrieval

[1]  Kihyun Hong,et al.  Legal content fusion for legal information retrieval , 2017, ICAIL.

[2]  Ralph Grishman,et al.  Towards Best Practice for Multiword Expressions in Computational Lexicons , 2002, LREC.

[3]  James Allan,et al.  Document classification using multiword features , 1998, CIKM '98.

[4]  James Allan,et al.  A comparison of sentence retrieval techniques , 2007, SIGIR.

[5]  William A. Woods,et al.  Context-sensitive parsing , 1970, CACM.

[6]  G Salton,et al.  Automatic Analysis, Theme Generation, and Summarization of Machine-Readable Texts , 1994, Science.

[7]  Norbert Fuhr,et al.  Integration of probabilistic fact and text retrieval , 1992, SIGIR '92.

[8]  Janet L. Kolodner Requirements for natural language fact retrieval , 1982, ACM '82.

[9]  Fernando Pereira,et al.  Shallow Parsing with Conditional Random Fields , 2003, NAACL.

[10]  Wendy G. Lehnert,et al.  Information extraction , 1996, CACM.

[11]  Charles L.A. Clarke,et al.  SIGIR '07, Amsterdam : proceedings : 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, July 23-27, 2007, Amsterdam, the Netherlands , 2007 .

[12]  J. Shane Culpepper,et al.  Sketch-based indexing of n-words , 2012, CIKM.

[13]  Aline Villavicencio,et al.  Identification and Treatment of Multiword Expressions Applied to Information Retrieval , 2011, MWE@ACL.

[14]  W. Bruce Croft,et al.  Retrieving Passages and Finding Answers , 2014, ADCS '14.

[15]  Yiming Yang,et al.  Introducing the Enron Corpus , 2004, CEAS.

[16]  Ion Androutsopoulos,et al.  Extracting contract elements , 2017, ICAIL.

[17]  Asunción Gómez-Pérez,et al.  Ontology-based legal information retrieval to improve the information access in e-government , 2006, WWW '06.