- A Probabilistic Model for Understanding Composite Spoken Descriptions
- Exploratory Interaction with a Bayesian Argumentation System Ingrid Zukerman, Richard McConachy, Kevin Korb and Deborah Pickett
- Deciding What Not to Say: An Attentional-Probabilistic Approach to Argument Presentation
- An Integrated Approach for Generating Arguments and Rebuttals and Understanding Rejoinders
- A Probabilistic Approach to the Interpretation of Spoken Utterances
- Predictive Statistical Models for User Modeling INGRID ZUKERMAN and DAVID W. ALBRECHT
- Voting Policies that Cope with Unreliable Agents Collaboration plays a critical role when a team is striv-
- Pre-sending Documents on the WWW: A Comparative Study David Albrecht, Ingrid Zukerman and Ann Nicholson
- Bayesian Models for Keyhole Plan Recognition in an Adventure Game
- Towards the Interpretation of Utterance Sequences in a Dialogue System Ingrid Zukerman and Patrick Ye and Kapil Kumar Gupta and Enes Makalic
- Spatial Processes for Recommender Systems Fabian Bohnert, Daniel F. Schmidt, and Ingrid Zukerman
- Non-Intrusive Personalisation of the Museum Experience
- Analyzing the Effect of Query Class on Document Retrieval Performance
- Lexical Query Paraphrasing for Document Retrieval Ingrid Zukerman
- User Model User-Adap Inter (2007) 17:439474 DOI 10.1007/s11257-007-9034-9
- DOI 10.1007/s11257-004-5660-7 User Modeling and User-Adapted Interaction (2005) 15: 553 Springer 2005
- Modeling Suppositions in Users' Arguments Sarah George and Ingrid Zukerman and Michael Niemann
- Incorporating a User Model into an Information Theoretic Framework for Argument Interpretation
- Recognizing Intentions from Rejoinders in a Bayesian Interactive Argumentation System
- Bayesian Reasoning in an Abductive Mechanism for Argument Generation and Analysis
- ATTENTION DURING ARGUMENT GENERATION AND PRESENTATION
- A Cognitive Model of Argumentation Kevin B. Korb, Richard McConachy and Ingrid Zukerman
- Trading off Granularity against Complexity in Predictive Models for Complex Domains
- Predicting Users' Requests on the WWW I. Zukerman, D.W. Albrecht and A.E. Nicholson
- A predictive approach to help-desk response generation Yuval Marom and Ingrid Zukerman
- An Anytime Algorithm for Interpreting Arguments Sarah George, Ingrid Zukerman, and Michael Niemann
- Lexical Access for Speech Understanding using Minimum Message Length Encoding
- Query Expansion and Query Reduction in Document Retrieval Ingrid Zukerman
- A Minimum Message Length Approach for Argument Interpretation Ingrid Zukerman and Sarah George
- Assessing the Impact of Measurement Uncertainty on User Models in Spatial Domains
- Natural Language Processing and User Modeling: Synergies and Limitations
- Using Interest and Transition Models to Predict Visitor Locations in Museums
- A Meta-learning Approach for Selecting between Response Automation Strategies in a Help-desk Domain
- 984 UNSW Law Journal Volume 34(3) GHOSTS FROM THE HIGH COURT'S PAST
- Influence of Gestural Salience on the Interpretation of Spoken Requests Gideon Kowadlo, Patrick Ye, Ingrid Zukerman
- Marom, Yuval and Ingrid Zukerman. 2009. An empirical study of corpus-based response automation methods for an e-mail-based help-desk domain. Computational Linguistics, uncorrected proof.
