The integration of narrative and argumentation for a scenario-based learning environment in law
- Authors: Stranieri, Andrew , Yearwood, John
- Date: 2005
- Type: Text , Conference paper
- Relation: Paper presented at the Tenth International Conference on Artificial Intelligence and Law, Bologna, Italy : 6th - 11th June, 2005
- Full Text: false
- Reviewed:
- Description: Narrative or story telling has long been used to structure and organise human experience. In contrast to logical models of reasoning, narrative models enable complex situations to be understood and recalled by humans readily. There is also some indication that narrative models represent the way in which jurors weigh up the veracity of legal evidence. In this work a narrative model is integrated into a logical reasoning model for the purpose of advancing a learning environment that promises to be engaging and effective. The narrative model includes a representation of the point of a story and a simple story grammar. The learning environment is designed to enable the automated generation of plausible scenarios representing a variety of family law property division cases told from the point of view of numerous characters.
- Description: E1
- Description: 2003001432
Association rules and multiple variables in complex times series forecasting
- Authors: Bertoli, Marcello , Stranieri, Andrew , Banerjee, Arunava
- Date: 2004
- Type: Text , Conference paper
- Relation: Paper presented at the First International Workshop on Intelligent Finance, IWIF1, Melbourne : 13th December, 2004
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000847
Forecasting on complex datasets with association rules
- Authors: Bertoli, Marcello , Stranieri, Andrew
- Date: 2004
- Type: Text , Conference paper
- Relation: Paper presented at Knowledge-Based Intelligent Information & Engineering Systems: 8th International Conference, KES 2004, Proceedings, Part I, Wellington, New Zealand : 21st September, 2004
- Full Text: false
- Reviewed:
- Description: Forecasting in complex fields such as financial markets or national economies is made difficult by the impact of numerous variables with unknown inter-dependencies. A forecasting approach is presented that produces forecasts on a variable based on past values for that variable and other, possibly inter-dependent variables. The approach is based on the intuition that the next value in a series depends on the last value and the last two values and the last three values and so on. Furthermore, the next value depends also on past values on other variables. No assumptions about the form of functions underpinning a dataset are made. Rather, evidence for each possible next value is collected by combining confidence values of numerous association rules. The approach has been evaluated by forecasting values in a hypothetical dataset and by forecasting the direction of the Australian stock market index with favorable results.
- Description: E1
- Description: 2003000849
Scenario-based learning environments
- Authors: Yearwood, John , Stranieri, Andrew
- Date: 2004
- Type: Text , Conference paper
- Relation: Paper presented at the Narrative and Interactive Learning Environments conference, NILE 2004, Edinburgh, Scotland : 10th August, 2004
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000832
Web-based decision support for structured reasoning in health
- Authors: Stranieri, Andrew , Yearwood, John , Gervasoni, Susan , Garner, Susan , Deans, Cecil , Johnstone, Alistair
- Date: 2004
- Type: Text , Conference paper
- Relation: Paper presented at Health Informatics Conference 2004 - Let's make a difference with health ICT, Brisbane, Queensland : 25th July, 2004
- Full Text: false
- Reviewed:
- Description: Decision making processes in the health care setting are often complex, demanding of professionals and rapidly changing. Furthermore, there is increasing pressure for professionals to make reasoning transparent and consistent. Decision support technologies have not made a substantial contribution to these issues to date largely because knowledge is difficult to elicit and maintain and existing development tools are very sophisticated yet complex. In this study a method for representing complex and discretionary reasoning used successfully in law was applied to the task of modelling decision making processes that critical care nurses deploy in responding to a low oxygen alarm. The approach, based on decision and argument tree diagrams enables the rapid development of small scale, yet useful web based decision support systems.
- Description: E1
- Description: 2003000831
Visualizing association rules for feedback within the legal system
- Authors: Ivkovic, Sasha , Yearwood, John , Stranieri, Andrew
- Date: 2003
- Type: Text , Conference paper
- Relation: Paper presented at the 9th International Conference on Artificial Intelligence and Law, Edinburgh, Scotland : 24th - 28th June, 2003
- Full Text: false
- Reviewed:
- Description: Knowledge discovery from databases (KDD) exercises in law have typically attempted to derive knowledge about decision making processes in the legal domain automatically from datasets. This is made difficult in that real data that represents aspects of a decision process in law is commonly stored as text and rarely stored in structured databases. The central claim advanced here is that KDD processes can be usefully applied to existing datasets of client and demographic data in order to provide feedback for the effective operation of organizations within the legal system. However, the cost of data mining suites and the scarcity of specialized personnel for these tools mitigates against their use. In this study data mining with Association Rules (AR) has been performed on a data-set of over 380,000 records from a legal aid agency. Methods to visualise patterns in order to suggest and test plausible hypotheses from the data have been developed. The tool, called WebAssociate is entirely web based. Domain experts using the tool report favorable responses.
- Description: E1
- Description: 2003000495
An argumentation shell for supporting the development and drafting of legal arguments
- Authors: Yearwood, John , Stranieri, Andrew
- Date: 2002
- Type: Text , Journal article
- Relation: Information and Communication Technology Law Vol. 11, no. 1 (2002), p. 75-86
- Full Text: false
- Reviewed:
- Description: This article describes an argumentation shell to support the formulation, representation and drafting of legal arguments. The shell can be used to capture generic arguments in many legal domains as well as to assist decision-makers in constructing their own actual arguments . The shell demonstrates that knowledge represented using the generic/actual argument model (GAAM) (a variant of Toulmin's argument structure) can be used to: (a) support the development of complex arguments, (b) add context and increase specificity for the retrieval of relevant documents, (c) incorporate background knowledge, (d) assist in the drafting of documents that represent arguments made, and (e) provide a structure for complex inferences requiring a range of mechanisms. The shell can be used to support decision making in a range of legal domains, including discretionary domains.
- Description: C1
- Description: 2003000141
Discovering interesting association rules from legal databases
- Authors: Ivkovic, Sasha , Yearwood, John , Stranieri, Andrew
- Date: 2002
- Type: Text , Journal article
- Relation: Information & Communication Technology Law Vol. 11, no. 1 (2002), p. 35-47
- Full Text:
- Reviewed:
- Description: The Knowledge Discovery from Databases (KDD) technique called 'association rules' is applied to a large data set representing applicants for government-funded legal aid. Results indicate that KDD can be an invaluable tool for legal analysts. Association rules discovered identify associations between variables that are present in the data set though are not necessarily causal. Interesting rules can prompt analysts to formulate hypotheses for further investigation. The identification of interesting rules is typically performed using an objective measure of 'interesting' although this measure is often not sufficiently accurate to eliminate all uninteresting rules. In this article, a subjective measure of interestingness is adopted in conjunction with the objective measures. This leads to the ability to focus more accurately on those rules that surprise the analyst and are therefore more likely to be interesting. In general, KDD techniques have not been applied to law despite possible benefits because data is often stored in narrative form rather than in structured databases. However, the impending introduction of data warehouses that collect data from a number of organizations across a legal system presents invaluable opportunities for analysts using KDD.
- Description: C1
- Description: 2003000037
Generic arguments : A framework for supporting online deliberative discourse
- Authors: Yearwood, John , Stranieri, Andrew
- Date: 2002
- Type: Text , Conference paper
- Relation: Paper presented at the Thirteenth Australasian Conference on Information Systems, Melbourne : 4th December, 2002
- Full Text:
- Reviewed:
- Description: In this paper we propose a framework based on argumentation that can be used to support deliberative discourse on line. Online communities have several distinct advantages as very open forums but they also have some deep disadvantages. We argue that the proposed framework and web application GAAMtalk permits and encourages the positive elements of online deliberation that will enhance discussions.
- Description: E1
- Description: 2003000114
A global optimisation approach to classification in medical diagnosis and prognosis
- Authors: Bagirov, Adil , Rubinov, Alex , Yearwood, John , Stranieri, Andrew
- Date: 2001
- Type: Text , Conference paper
- Relation: Paper presented at 34th Hawaii International Conference on System Sciences, HICSS-34, Maui, Hawaii, USA : 3rd-6th January 2001
- Full Text:
- Description: In this paper global optimisation-based techniques are studied in order to increase the accuracy of medical diagnosis and prognosis with FNA image data from the Wisconsin Diagnostic and Prognostic Breast Cancer databases. First we discuss the problem of determining the most informative features for the classification of cancerous cases in the databases under consideration. Then we apply a technique based on convex and global optimisation to breast cancer diagnosis. It allows the classification of benign cases and malignant ones and the subsequent diagnosis of patients with very high accuracy. The third application of this technique is a method that calculates centres of clusters to predict when breast cancer is likely to recur in patients for which cancer has been removed. The technique achieves higher accuracy with these databases than reported elsewhere in the literature.
- Description: 2003003950
An argumentation-based multi-agent system for e-tourism dialogue
- Authors: Avery, John , Yearwood, John , Stranieri, Andrew
- Date: 2001
- Type: Text , Conference paper
- Relation: Paper presented at Hybrid Information Systems, First International Workshop on Hybrid Intelligent Systems, Adelaide : 11th - 12th December, 2003 p. 497-512
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000112
Argumentation structures that integrate dialectical and non-dialectical reasoning
- Authors: Stranieri, Andrew , Zeleznikow, John , Yearwood, John
- Date: 2001
- Type: Text , Journal article
- Relation: Knowledge Engineering Review Vol. 16, no. 4 (Dec 2001), p. 331-348
- Full Text:
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- Description: Argumentation concepts have been applied to numerous knowledge engineering endeavours in recent years. For example, a variety of logics have been developed to represent argumentation in the context of a dialectical situation such as a dialogue. In contrast to the dialectical approach, argumentation has also been used to structure knowledge. This can be seen as a non-dialectical approach. The Toulmin argument structure has often been used to structure knowledge non-dialectically yet most studies that apply the Toulmin structure do not use the original structure but vary one or more components. Variations to the Toulmin structure can be understood as different ways to integrate a dialectical perspective with a non-dialectical one. Drawing the dialectical/non-dialectical distinction enables the specification of a framework called the generic actual argument model that is expressly non-dialectical. The framework enables the development of knowledge-based systems that integrate a variety of inference procedures, combine information retrieval with reasoning and facilitate automated document drafting. Furthermore, the non-dialectical framework provides the foundation for simple dialectical models. Systems based on our approach have been developed in family law, refugee law, determining eligibility for government legal aid, copyright law and e-tourism.
- Description: C1
- Description: 2003002516
Tools for placing legal decision support systems on the world wide web
- Authors: Stranieri, Andrew , Yearwood, John , Zeleznikow, John
- Date: 2001
- Type: Text , Conference paper
- Relation: Paper presented at Eighth International Conference on Artificial Intelligence and Law, ICAIL 2001, St. Louis, USA : 21st-25th May 2001
- Full Text: false
- Description: 2003003944