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Semantic ScholarIngrid Zukerman
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- affiliation: Monash University, Melbourne, Australia
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2010 – today
- 2018
[j30]Kai Zhan, Ingrid Zukerman, Andisheh Partovi:
Identifying factors that influence the acceptability of smart devices: implications for recommendations. User Model. User-Adapt. Interact. 28(4-5): 391-423 (2018)- [c113]Quan Hung Tran, Tuan Lai, Gholamreza Haffari, Ingrid Zukerman, Trung Bui, Hung Bui:
The Context-Dependent Additive Recurrent Neural Net. NAACL-HLT 2018: 1274-1283 - [i4]Xuanli He, Quan Hung Tran, William Havard, Laurent Besacier, Ingrid Zukerman, Gholamreza Haffari:
Exploring Textual and Speech information in Dialogue Act Classification with Speaker Domain Adaptation. CoRR abs/1810.07455 (2018) - 2017
- [j29]Ingrid Zukerman, Andisheh Partovi:
Improving the understanding of spoken referring expressions through syntactic-semantic and contextual-phonetic error-correction. Computer Speech & Language 46: 284-310 (2017) - [c112]Quan Hung Tran, Gholamreza Haffari, Ingrid Zukerman:
A Generative Attentional Neural Network Model for Dialogue Act Classification. ACL (2) 2017: 524-529 - [c111]Ingrid Zukerman, Gholamreza Haffari, Quan Hung Tran:
A Hierarchical Neural Model for Learning Sequences of Dialogue Acts. EACL (1) 2017: 428-437 - [c110]Quan Hung Tran, Ingrid Zukerman, Gholamreza Haffari:
Preserving Distributional Information in Dialogue Act Classification. EMNLP 2017: 2151-2156 - [c109]Ingrid Zukerman, Andisheh Partovi, Kai Zhan, Nora Hamacher, Julie Stout, Masud Moshtaghi:
A Game for Eliciting Trust Between People and Devices Under Diverse Performance Conditions. CGW@IJCAI 2017: 172-190 - 2016
- [j28]Simon Kocbek, Lawrence Cavedon, David Martínez, Christopher Bain, Chris Mac Manus, Gholamreza Haffari, Ingrid Zukerman, Karin Verspoor:
Text mining electronic hospital records to automatically classify admissions against disease: Measuring the impact of linking data sources. Journal of Biomedical Informatics 64: 158-167 (2016) - [c108]Tatyana Shmanina, Ingrid Zukerman, Ai Lee Cheam, Thomas Bochynek, Lawrence Cavedon:
A Corpus of Tables in Full-Text Biomedical Research Publications. BioTxtM@COLING 2016 2016: 70-79 - [c107]Quan Hung Tran, Ingrid Zukerman, Gholamreza Haffari:
Inter-document Contextual Language model. HLT-NAACL 2016: 762-766 - [c106]Kai Zhan, Ingrid Zukerman, Masud Moshtaghi, Gwyneth Rees:
Eliciting Users' Attitudes toward Smart Devices. UMAP 2016: 175-184 - 2015
- [j27]Ingrid Zukerman, Su Nam Kim, Thomas Kleinbauer, Masud Moshtaghi:
Employing distance-based semantics to interpret spoken referring expressions. Computer Speech & Language 34(1): 154-185 (2015) - [j26]Masud Moshtaghi, Ingrid Zukerman, R. Andrew Russell:
Statistical models for unobtrusively detecting abnormal periods of inactivity in older adults. User Model. User-Adapt. Interact. 25(3): 231-265 (2015) - [c105]Ingrid Zukerman, Andisheh Partovi, Su Nam Kim:
Context-dependent error correction of spoken referring expressions. INTERSPEECH 2015: 2032-2036 - [c104]Masud Moshtaghi, Ingrid Zukerman:
A Utility Model for Tailoring Sensor Networks to Users. UMAP 2015: 156-168 - 2014
- [j25]Yanir Seroussi, Ingrid Zukerman, Fabian Bohnert:
Authorship Attribution with Topic Models. Computational Linguistics 40(2): 269-310 (2014) - [j24]Melanie Frances Larizza, Ingrid Zukerman, Fabian Bohnert, Lucy Busija, Sharon Ann Bentley, R. Andrew Russell, Gwyneth Rees:
In-home monitoring of older adults with vision impairment: exploring patients', caregivers' and professionals' views. JAMIA 21(1): 56-63 (2014) - [j23]Fabian Bohnert, Ingrid Zukerman:
Personalised viewing-time prediction in museums. User Model. User-Adapt. Interact. 24(4): 263-314 (2014) - [c103]Su Nam Kim, Ingrid Zukerman, Thomas Kleinbauer, Masud Moshtaghi:
A Comparative Study of Weighting Schemes for the Interpretation of Spoken Referring Expressions. ALTA 2014: 50-58 - [c102]Tatyana Shmanina, Lawrence Cavedon, Ingrid Zukerman:
Challenges in Information Extraction from Tables in Biomedical Research Publications: a Dataset Analysis. ALTA 2014: 118-122 - [c101]Masud Moshtaghi, Ingrid Zukerman:
Modeling the Tail of a Hyperexponential Distribution to Detect Abnormal Periods of Inactivity in Older Adults. PRICAI 2014: 985-997 - 2013
- [c100]Tatyana Shmanina, Ingrid Zukerman, Antonio Jimeno-Yepes, Lawrence Cavedon, Karin Verspoor:
Impact of Corpus Diversity and Complexity on NER Performance. ALTA 2013: 91-95 - [c99]Farshid Zavareh, Ingrid Zukerman, Su Nam Kim, Thomas Kleinbauer:
Error Detection in Automatic Speech Recognition. ALTA 2013: 101-105 - [c98]Thomas Kleinbauer, Ingrid Zukerman, Su Nam Kim:
Evaluation of the Scusi? Spoken Language Interpretation System - A Case Study. IJCNLP 2013: 225-233 - [c97]Su Nam Kim, Ingrid Zukerman, Thomas Kleinbauer, Farshid Zavareh:
A Noisy Channel Approach to Error Correction in Spoken Referring Expressions. IJCNLP 2013: 234-242 - [c96]Masud Moshtaghi, Ingrid Zukerman, David W. Albrecht, R. Andrew Russell:
Monitoring Personal Safety by Unobtrusively Detecting Unusual Periods of Inactivity. UMAP 2013: 139-151 - [i3]Ian E. Thomas, Ingrid Zukerman, Jonathan J. Oliver, David W. Albrecht, Bhavani Raskutti:
Lexical Access for Speech Understanding using Minimum Message Length Encoding. CoRR abs/1302.1572 (2013) - [i2]Bhavani Raskutti, Ingrid Zukerman:
Handling Uncertainty during Plan Recognition in Task-Oriented Consultation Systems. CoRR abs/1303.5743 (2013) - [i1]Peter Sember, Ingrid Zukerman:
Strategies for Generating Micro Explanations for Bayesian Belief Networks. CoRR abs/1304.1524 (2013) - 2012
- [c95]Yanir Seroussi, Fabian Bohnert, Ingrid Zukerman:
Authorship Attribution with Author-aware Topic Models. ACL (2) 2012: 264-269 - [c94]Minh Duc Cao, Ingrid Zukerman:
Experimental Evaluation of a Lexicon- and Corpus-based Ensemble for Multi-way Sentiment Analysis. ALTA 2012: 52-60 - [c93]Fabian Bohnert, Ingrid Zukerman, David W. Albrecht:
Realistic Simulation of Museum Visitors' Movements as a Tool for Assessing Sensor-Based User Models. UMAP 2012: 14-25 - [c92]Fabian Bohnert, Ingrid Zukerman, Junaidy Laures:
GECKOmmender: Personalised Theme and Tour Recommendations for Museums. UMAP 2012: 26-37 - [c91]Melanie Frances Larizza, Ingrid Zukerman, Fabian Bohnert, R. Andrew Russell, Lucy Busija, David W. Albrecht, Gwyn Rees:
Studies to Determine User Requirements Regarding In-Home Monitoring Systems. UMAP 2012: 139-150 - 2011
- [j22]Stephanie Elzer, Sandra Carberry, Ingrid Zukerman:
The automated understanding of simple bar charts. Artif. Intell. 175(2): 526-555 (2011) - [c90]Yanir Seroussi, Ingrid Zukerman, Fabian Bohnert:
Authorship Attribution with Latent Dirichlet Allocation. CoNLL 2011: 181-189 - [c89]Yanir Seroussi, Fabian Bohnert, Ingrid Zukerman:
Personalised rating prediction for new users using latent factor models. HT 2011: 47-56 - [c88]Timothy Baldwin, Patrick Ye, Fabian Bohnert, Ingrid Zukerman:
In Situ Text Summarisation for Museum Visitors. PACLIC 2011: 372-381 - 2010
- [c87]Adrian Bickerstaffe, Ingrid Zukerman:
A Hierarchical Classifier Applied to Multi-way Sentiment Detection. COLING 2010: 62-70 - [c86]Ingrid Zukerman, Gideon Kowadlo, Patrick Ye:
Interpreting Pointing Gestures and Spoken Requests - A Probabilistic, Salience-based Approach. COLING (Posters) 2010: 1558-1566 - [c85]Gideon Kowadlo, Patrick Ye, Ingrid Zukerman:
Influence of gestural salience on the interpretation of spoken requests. INTERSPEECH 2010: 2034-2037 - [c84]Fabian Bohnert, Ingrid Zukerman:
A User-and Item-Aware Weighting Scheme for Combining Predictive User Models. UMAP 2010: 99-110 - [c83]Yanir Seroussi, Ingrid Zukerman, Fabian Bohnert:
Collaborative Inference of Sentiments from Texts. UMAP 2010: 195-206 - [c82]
2000 – 2009
- 2009
- [j21]Yuval Marom, Ingrid Zukerman:
An Empirical Study of Corpus-Based Response Automation Methods for an E-mail-Based Help-Desk Domain. Computational Linguistics 35(4): 597-635 (2009) - [c81]Patrick Ye, Ingrid Zukerman:
Towards Interpreting Task-Oriented Utterance Sequences. Australasian Conference on Artificial Intelligence 2009: 607-616 - [c80]Fabian Bohnert, Ingrid Zukerman:
Using Keyword-Based Approaches to Adaptively Predict Interest in Museum Exhibits. Australasian Conference on Artificial Intelligence 2009: 656-665 - [c79]Fabian Bohnert, Daniel Francis Schmidt, Ingrid Zukerman:
Spatial Processes for Recommender Systems. IJCAI 2009: 2022-2027 - [c78]Fabian Bohnert, Ingrid Zukerman, Daniel Francis Schmidt:
Using Gaussian Spatial Processes to Model and Predict Interests in Museum Exhibits. ITWP 2009 - [c77]Ingrid Zukerman, Patrick Ye, Kapil Kumar Gupta, Enes Makalic:
Towards the Interpretation of Utterance Sequences in a Dialogue System. SIGDIAL Conference 2009: 46-53 - [c76]Fabian Bohnert, Ingrid Zukerman:
Non-intrusive Personalisation of the Museum Experience. UMAP 2009: 197-209 - [c75]Daniel Francis Schmidt, Ingrid Zukerman, David W. Albrecht:
Assessing the Impact of Measurement Uncertainty on User Models in Spatial Domains. UMAP 2009: 210-222 - [p1]Ingrid Zukerman:
Towards Probabilistic Argumentation. Argumentation in Artificial Intelligence 2009: 443-462 - 2008
- [j20]Fabian Bohnert, Ingrid Zukerman, Shlomo Berkovsky, Timothy Baldwin, Liz Sonenberg:
Using interest and transition models to predict visitor locations in museums. AI Commun. 21(2-3): 195-202 (2008) - [c74]Fabian Bohnert, Ingrid Zukerman, Shlomo Berkovsky, Timothy Baldwin, Liz Sonenberg:
Using Collaborative Models to Adaptively Predict Visitor Locations in Museums. AH 2008: 42-51 - [c73]Shlomo Berkovsky, Timothy Baldwin, Ingrid Zukerman:
Aspect-Based Personalized Text Summarization. AH 2008: 267-270 - [c72]Ingrid Zukerman, Enes Makalic, Michael Niemann:
Using Probabilistic Feature Matching to Understand Spoken Descriptions. Australasian Conference on Artificial Intelligence 2008: 157-167 - [c71]Enes Makalic, Ingrid Zukerman, Michael Niemann:
A spoken language interpretation component for a robot dialogue system. INTERSPEECH 2008: 195-198 - [c70]Ingrid Zukerman, Enes Makalic, Michael Niemann, Sarah George:
A Probabilistic Approach to the Interpretation of Spoken Utterances. PRICAI 2008: 581-592 - [c69]Enes Makalic, Ingrid Zukerman, Michael Niemann, Daniel Francis Schmidt:
A Probabilistic Model for Understanding Composite Spoken Descriptions. PRICAI 2008: 750-759 - 2007
- [j19]David W. Albrecht, Ingrid Zukerman:
Introduction to the special issue on statistical and probabilistic methods for user modeling. User Model. User-Adapt. Interact. 17(1-2): 1-4 (2007) - [j18]Sarah George, Ingrid Zukerman, Michael Niemann:
Inferences, suppositions and explanatory extensions in argument interpretation. User Model. User-Adapt. Interact. 17(5): 439-474 (2007) - [c68]Yuval Marom, Ingrid Zukerman, Nathalie Japkowicz:
A Meta-learning Approach for Selecting between Response Automation Strategies in a Help-desk Domain. AAAI 2007: 907-912 - [c67]Fabian Bohnert, Ingrid Zukerman:
Using Viewing Time for Theme Prediction in Cultural Heritage Spaces. Australian Conference on Artificial Intelligence 2007: 367-376 - [c66]Michael Niemann, Ingrid Zukerman, Enes Makalic, Sarah George:
Hypothesis Generation and Maintenance in the Interpretation of Spoken Utterances. Australian Conference on Artificial Intelligence 2007: 466-475 - [c65]Yuval Marom, Ingrid Zukerman:
A Predictive Approach to Help-Desk Response Generation. IJCAI 2007: 1665-1670 - 2006
- [j17]Christian Guttmann, Ingrid Zukerman:
Agents with limited modeling abilities: Implications on collaborative problem solving. Comput. Syst. Sci. Eng. 21(3) (2006) - [c64]Ingrid Zukerman, Yuval Marom:
A Comparative Study of Information-Gathering Approaches for Answering Help-Desk Email Inquiries. Australian Conference on Artificial Intelligence 2006: 546-556 - [c63]Ingrid Zukerman, Michael Niemann, Sarah George, Yuval Marom:
Probabilistic, Multi-staged Interpretation of Spoken Utterances. Australian Conference on Artificial Intelligence 2006: 1215-1220 - [c62]Ingrid Zukerman, Yuval Marom:
A corpus-based approach to help-desk response generation. CIMCA/IAWTIC 2006: 23 - [c61]Ingrid Zukerman, Michael Niemann, Sarah George:
Probabilistic, Multi-staged Interpretation of Spoken Utterances. CIMCA/IAWTIC 2006: 194 - [c60]Ingrid Zukerman, Michael Niemann, Sarah George:
Balancing Conflicting Factors in Argument Interpretation. SIGDIAL Workshop 2006: 134-143 - [e1]Lawrence Cavedon, Ingrid Zukerman:
Proceedings of the Australasian Language Technology Workshop, ALTA 2006, Sydney, Australia, November 30-December 1, 2006. Australasian Language Technology Association 2006, ISBN 978-1-74108-146-6 [contents] - 2005
- [j16]Ingrid Zukerman:
Argumentation Machines: New Frontiers in Argumentation and Computation edited by Chris ReedTimothy J. Norman. Computational Linguistics 31(1): 153-155 (2005) - [j15]Sandra Carberry, Ingrid Zukerman:
Preface to the Special Issue on Language-Based Interaction. User Model. User-Adapt. Interact. 15(1-2): 1-3 (2005) - [j14]Ingrid Zukerman, Sarah George:
A Probabilistic Approach for Argument Interpretation. User Model. User-Adapt. Interact. 15(1-2): 5-53 (2005) - [c59]Stephanie Elzer, Sandra Carberry, Daniel Chester, Seniz Demir, Nancy Green, Ingrid Zukerman, Keith Trnka:
Exploring and Exploiting the Limited Utility of Captions in Recognizing Intention in Information Graphics. ACL 2005: 223-230 - [c58]Christian Guttmann, Ingrid Zukerman:
Voting policies that cope with unreliable agents. AAMAS 2005: 365-372 - [c57]Stephanie Elzer, Sandra Carberry, Ingrid Zukerman, Daniel Chester, Nancy Green, Seniz Demir:
A Probabilistic Framework for Recognizing Intention in Information Graphics. IJCAI 2005: 1042-1047 - [c56]
- [c55]Sarah George, Ingrid Zukerman, Michael Niemann:
Modeling Suppositions in Users' Arguments. User Modeling 2005: 19-29 - [c54]Ingrid Zukerman, Christian Guttmann:
Modeling Agents That Exhibit Variable Performance in a Collaborative Setting. User Modeling 2005: 210-219 - 2004
- [c53]Pawel Kowalczyk, Ingrid Zukerman, Michael Niemann:
Analyzing the Effect of Query Class on Document Retrieval Performance. Australian Conference on Artificial Intelligence 2004: 550-561 - [c52]Ingrid Zukerman, Michael Niemann, Sarah George:
Improving the Presentation of Argument Interpretations Based on User Trials. Australian Conference on Artificial Intelligence 2004: 587-598 - [c51]Ingrid Zukerman, Yuval Marom:
Filtering Speaker-Specific Words from Electronic Discussions. COLING 2004 - [c50]Christian Guttmann, Ingrid Zukerman:
Towards Models of Incomplete and Uncertain Knowledge of Collaborators' Internal Resources. MATES 2004: 58-72 - [c49]Sarah George, Ingrid Zukerman, Michael Niemann:
An Anytime Algorithm for Interpreting Arguments. PRICAI 2004: 311-321 - [c48]Yuval Marom, Ingrid Zukerman:
Improving Newsgroup Clustering by Filtering Author-Specific Words. PRICAI 2004: 953-954 - 2003
- [c47]Ingrid Zukerman, Sarah George, Yingying Wen:
Lexical Paraphrasing for Document Retrieval and Node Identification. IWP@ACL 2003 - [c46]Sarah George, Ingrid Zukerman, Mark George:
An information-theoretic approach for argument interpretation in a conversational setting. AAMAS 2003: 992-993 - [c45]Ingrid Zukerman, Bhavani Raskutti, Yingying Wen:
Query Expansion and Query Reduction in Document Retrieval. ICTAI 2003: 552-559 - [c44]Sarah George, Ingrid Zukerman:
An Information-theoretic Approach for Argument Interpretation. SIGDIAL Workshop 2003: 44-52 - [c43]Ingrid Zukerman, Sarah George, Mark George:
Incorporating a User Model into an Information Theoretic Framework for Argument Interpretation. User Modeling 2003: 106-116 - 2002
- [c42]Ingrid Zukerman, Bhavani Raskutti, Yingying Wen:
Experiments in Query Paraphrasing for Information Retrieval. Australian Joint Conference on Artificial Intelligence 2002: 24-35 - [c41]Sarah George, Ingrid Zukerman:
Argument Interpretation Using Minimum Message Length. Australian Joint Conference on Artificial Intelligence 2002: 297-308 - [c40]Ingrid Zukerman, Sarah George:
Towards a Noise-Tolerant, Representation-Independent Mechanism for Argument Interpretation. COLING 2002 - [c39]
- [c38]Werner Winiwarter, Ingrid Zukerman, Tsunenori Mine:
Message from the NLIS Workshop Chairs. DEXA Workshops 2002: 201-204 - [c37]Ingrid Zukerman, Sarah George:
A Minimum Message Length Approach for Argument Interpretation. SIGDIAL Workshop 2002: 211-220 - 2001
- [j13]Ingrid Zukerman, Richard McConachy:
Wishful: A Discourse Planning System That Considers a User's Inferences. Computational Intelligence 17(1): 1-61 (2001) - [j12]Ingrid Zukerman, David W. Albrecht:
Predictive Statistical Models for User Modeling. User Model. User-Adapt. Interact. 11(1-2): 5-18 (2001) - [j11]Ingrid Zukerman, Diane J. Litman:
Natural Language Processing and User Modeling: Synergies and Limitations. User Model. User-Adapt. Interact. 11(1-2): 129-158 (2001) - [c36]Ariel E. Bud, David W. Albrecht, Ann E. Nicholson, Ingrid Zukerman:
Information-Theoretic Advisors in Invisible Chess. AISTATS 2001 - [c35]Ingrid Zukerman:
An Integrated Approach for Generating Arguments and Rebuttals and Understanding Rejoinders. User Modeling 2001: 84-94 - 2000
- [c34]Nathalie Jitnah, Ingrid Zukerman, Richard McConachy, Sarah George:
Towards the Generation of Rebuttals in a Bayesian Argumentation System. INLG 2000: 39-46 - [c33]Ingrid Zukerman, Richard McConachy, Sarah George:
Using Argumentation Strategies in Automated Argument Generation. INLG 2000: 55-62 - [c32]Ingrid Zukerman, David W. Albrecht, Ann E. Nicholson, Krystyna Doktor:
Trading Off Granularity against Complexity. PRICAI 2000: 241-251 - [c31]Ingrid Zukerman, Nathalie Jitnah, Richard McConachy, Sarah George:
Recognizing Intentions from Rejoinders in a Bayesian Interactive Argumentation System. PRICAI 2000: 252-263
1990 – 1999
- 1999
- [j10]Richard McConachy, Ingrid Zukerman:
Dialogue Requirements for Argumentation Systems. Electron. Trans. Artif. Intell. 3(D): 89-124 (1999) - [c30]David W. Albrecht, Ingrid Zukerman, Ann E. Nicholson:
Pre-sending Documents on the WWW: A Comparative Study. IJCAI 1999: 1274-1279 - [c29]Ingrid Zukerman, Richard McConachy, Kevin B. Korb, Deborah Pickett:
Exploratory Interaction with a Bayesian Argumentation System. IJCAI 1999: 1294-1299 - [c28]Ariel E. Bud, Ann E. Nicholson, Ingrid Zukerman, David W. Albrecht:
A hybrid architecture for strategically complex imperfect information games. KES 1999: 42-45 - 1998
- [j9]Christopher Leckie, Ingrid Zukerman:
Inductive Learning of Search Control Rules for Planning. Artif. Intell. 101(1-2): 63-98 (1998) - [j8]David W. Albrecht, Ingrid Zukerman, Ann E. Nicholson:
Bayesian Models for Keyhole Plan Recognition in an Adventure Game. User Model. User-Adapt. Interact. 8(1-2): 5-47 (1998) - [c27]Ingrid Zukerman, Richard McConachy, Kevin B. Korb:
Bayesian Reasoning in an Abductive Mechanism for Argument Generation and Analysis. AAAI/IAAI 1998: 833-838 - [c26]Richard McConachy, Kevin B. Korb, Ingrid Zukerman:
A Bayesian Approach to Automating Argumentation. CoNLL 1998: 91-100 - [c25]Ian E. Thomas, Ingrid Zukerman, Bhavani Raskutti:
Extracting Phoneme Pronunciation Information from Corpora. CoNLL 1998: 175-184 - [c24]Ingrid Zukerman, Richard McConachy, Kevin B. Korb:
Attention During Argument Generation And Presentation. INLG 1998 - [c23]David W. Albrecht, Ann E. Nicholson, Ingrid Zukerman:
Knowledge Acquisition for Goal Prediction in a Multi-user Adventure Game. PAKDD 1998: 1-12 - [c22]Ann E. Nicholson, Ingrid Zukerman, David W. Albrecht:
A Decision-Theoretic Approach for Pre-sending Information on the WWW. PRICAI 1998: 575-586 - 1997
- [j7]Kristiina Jokinen, Mark T. Maybury, Michael Zock, Ingrid Zukerman:
Gaps and Bridges: New Directions in Planning and Natural Language Generation (Workshop Report). AI Magazine 18(1): 133-136 (1997) - [j6]Yi Han, Ingrid Zukerman:
Using constraint propagation in MAGPIE: a multi-agent approach. Computer Standards & Interfaces 18(6-7): 575-582 (1997) - [j5]Yi Han, Ingrid Zukerman:
A mechanism for Multimodal Presentation Planning Based on Agent Cooperation and Negotiation. Human-Computer Interaction 12(1-2): 187-226 (1997) - [j4]Bhavani Raskutti, Ingrid Zukerman:
Generating queries and replies during information-seeking interactions. Int. J. Hum.-Comput. Stud. 47(6): 689-734 (1997) - [c21]