Article Free Access Share on COREL: a conceptual retrieval system Authors: M. Kathryn Di Benigno JAYCOR, c/o Naval Research Laboratory, NOARAI - Code 7510, Washington, D.C. and Computer Science Department, Louisiana State University, Baton Rouge, LA JAYCOR, c/o Naval Research Laboratory, NOARAI - Code 7510, Washington, D.C. and Computer Science Department, Louisiana State University, Baton Rouge, LAView Profile , George R. Cross Computer Science Department, Washington State University, Pullman, WA Computer Science Department, Washington State University, Pullman, WAView Profile , Cary G. de Bessonet Law and AI Project, Louisiana State Law Institute, LSU Law Center, University Station, Baton Rouge, LA Law and AI Project, Louisiana State Law Institute, LSU Law Center, University Station, Baton Rouge, LAView Profile Authors Info & Claims SIGIR '86: Proceedings of the 9th annual international ACM SIGIR conference on Research and development in information retrievalSeptember 1986 Pages 144–148https://doi.org/10.1145/253168.253199Published:01 September 1986Publication History 6citation265DownloadsMetricsTotal Citations6Total Downloads265Last 12 Months12Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

The development of intelligent legal information processing systems depends critically on availability of representations of legal knowledge. Some of the application areas envisioned for intelligent legal systems include retrieval systems, argument and reasoning systems, legal decision-making systems, and drafting systems. Successful implementation of systems of these types has been hampered by a lack of adequate knowledge representation for the underlying legal concepts. We need both representations of everyday situations and of subtle legal concepts like rights, duties, and contracts. This paper reviews some of the recent work in representing legal situations and discusses the special knowledge representation questions that arise in developing legal information processing systems. We concentrate on computational aspects of Hohfeldian concepts of rights and duties, deontic logic, representation of legal arguments, and the semantics of legal relations.

We consider a texture to be a stochastic, possibly periodic, two-dimensional image field. A texture model is a mathematical procedure capable of producing and describing a textured image. We explore the use of Markov random fields as texture models. The binomial model, where each point in the texture has a binomial distribution with parameter controlled by its neighbors and ``number of tries'' equal to the number of gray levels, was taken to be the basic model for the analysis. A method of generating samples from the binomial model is given, followed by a theoretical and practical analysis of the method's convergence. Examples show how the parameters of the Markov random field control the strength and direction of the clustering in the image. The power of the binomial model to produce blurry, sharp, line-like, and blob-like textures is demonstrated. Natural texture samples were digitized and their parameters were estimated under the Markov random field model. A hypothesis test was used for an objective assessment of goodness-of-fit under the Markov random field model. Overall, microtextures fit the model well. The estimated parameters of the natural textures were used as input to the generation procedure. The synthetic microtextures closely resembled their real counterparts, while the regular and inhomogeneous textures did not.