Can shallow semantic class information help answer passage retrieval?
- Authors: Ofoghi, Bahadorreza , Yearwood, John
- Date: 2009
- Type: Text , Conference paper
- Relation: Paper presented at 22nd Australasian Joint Conference, AI 2009: Advances in Artificial Intelligence, Melbourne, Victoria : 1st-4th December 2009 p. 587–596
- Full Text: false
- Description: In this paper, the effect of using semantic class overlap evidence in enhancing the passage retrieval effectiveness of question answering (QA) systems is tested. The semantic class overlap between questions and passages is measured by evoking FrameNet semantic frames using a shallow term-lookup procedure. We use the semantic class overlap evidence in two ways: i) fusing passage scores obtained from a baseline retrieval system with those obtained from the analysis of semantic class overlap (fusion-based approach), and ii) revising the passage scoring function of the baseline system by incorporating semantic class overlap evidence (revision-based approach). Our experiments with the TREC 2004 and 2006 datasets show that the revision-based approach significantly improves the passage retrieval effectiveness of the baseline system.
- Description: 2003007254
On the limitations of scalarisation for multi-objective reinforcement learning of Pareto fronts
- Authors: Vamplew, Peter , Yearwood, John , Dazeley, Richard , Berry, Adam
- Date: 2008
- Type: Text , Conference paper
- Relation: Paper presented at 21st Australasian Joint Conference on Artificial Intelligence, Auckland, New Zealand : 1st-5th December 2008 Vol. 5360, p. 372-378
- Full Text: false
- Description: Multiobjective reinforcement learning (MORL) extends RL to problems with multiple conflicting objectives. This paper argues for designing MORL systems to produce a set of solutions approximating the Pareto front, and shows that the common MORL technique of scalarisation has fundamental limitations when used to find Pareto-optimal policies. The work is supported by the presentation of three new MORL benchmarks with known Pareto fronts.
- Description: 2003006504
System development a la MODDE
- Authors: Meikle, Tunde , Yearwood, John
- Date: 2001
- Type: Text , Conference paper
- Relation: Paper presented at 8th International Conference on Artificial Intelligence and Law - ICAIL '01, St. Louis, Missouri, USA : 21st-25th May 2001 p. 99-103
- Full Text: false
- Description: This paper describes the MODDE (Model of Decision support system Design and Evaluation) framework in some detail. The work is in progress and is being currently applied to the EMBRACE project being developed for the Refugee Review Tribunal (RRT) of Australia. Refugee law is the general legal area we are working in, while the specific domain under investigation is that of the decision makers at the RRT. EMBRACE is a decision support system being designed to assist the RRT in maintaining consistency of decisions, and preserve discretion of decision makers as well as making it easier to cope with high volumes of work in decreasing time frames. The use of the MODDE framework is intended to facilitate systematic attention to important features of decision making in our specific legal domain and to provide a sound basis upon which to evaluate a part of the system intrinsic to user acceptance. Copyright 2001 ACM.
- Description: 2003003947
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