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Ingrid Zukerman Vis

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*2009
80EEFabian Bohnert, Daniel F. Schmidt, Ingrid Zukerman: Spatial Processes for Recommender Systems. IJCAI 2009: 2022-2027
79EEFabian Bohnert, Ingrid Zukerman: Non-intrusive Personalisation of the Museum Experience. UMAP 2009: 197-209
78EEDaniel F. Schmidt, Ingrid Zukerman, David W. Albrecht: Assessing the Impact of Measurement Uncertainty on User Models in Spatial Domains. UMAP 2009: 210-222
2008
77EEShlomo Berkovsky, Timothy Baldwin, Ingrid Zukerman: Aspect-Based Personalized Text Summarization. AH 2008: 267-270
76EEFabian Bohnert, Ingrid Zukerman, Shlomo Berkovsky, Timothy Baldwin, Liz Sonenberg: Using Collaborative Models to Adaptively Predict Visitor Locations in Museums. AH 2008: 42-51
75EEIngrid Zukerman, Enes Makalic, Michael Niemann: Using Probabilistic Feature Matching to Understand Spoken Descriptions. Australasian Conference on Artificial Intelligence 2008: 157-167
74EEIngrid Zukerman, Enes Makalic, Michael Niemann, Sarah George: A Probabilistic Approach to the Interpretation of Spoken Utterances. PRICAI 2008: 581-592
73EEEnes Makalic, Ingrid Zukerman, Michael Niemann, Daniel F. Schmidt: A Probabilistic Model for Understanding Composite Spoken Descriptions. PRICAI 2008: 750-759
72EEFabian 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)
2007
71 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
70EEFabian Bohnert, Ingrid Zukerman: Using Viewing Time for Theme Prediction in Cultural Heritage Spaces. Australian Conference on Artificial Intelligence 2007: 367-376
69EEMichael 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
68EEYuval Marom, Ingrid Zukerman: A Predictive Approach to Help-Desk Response Generation. IJCAI 2007: 1665-1670
67EEDavid 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)
66EESarah George, Ingrid Zukerman, Michael Niemann: Inferences, suppositions and explanatory extensions in argument interpretation. User Model. User-Adapt. Interact. 17(5): 439-474 (2007)
2006
65EEIngrid Zukerman, Michael Niemann, Sarah George, Yuval Marom: Probabilistic, Multi-staged Interpretation of Spoken Utterances. Australian Conference on Artificial Intelligence 2006: 1215-1220
64EEIngrid Zukerman, Yuval Marom: A Comparative Study of Information-Gathering Approaches for Answering Help-Desk Email Inquiries. Australian Conference on Artificial Intelligence 2006: 546-556
63EEIngrid Zukerman, Michael Niemann, Sarah George: Probabilistic, Multi-staged Interpretation of Spoken Utterances. CIMCA/IAWTIC 2006: 194
62EEIngrid Zukerman, Yuval Marom: A corpus-based approach to help-desk response generation. CIMCA/IAWTIC 2006: 23
2005
61EEChristian Guttmann, Ingrid Zukerman: Voting policies that cope with unreliable agents. AAMAS 2005: 365-372
60EEStephanie 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
59EEStephanie Elzer, Sandra Carberry, Ingrid Zukerman, Daniel Chester, Nancy Green, Seniz Demir: A Probabilistic Framework for Recognizing Intention in Information Graphics. IJCAI 2005: 1042-1047
58EEYuval Marom, Ingrid Zukerman: Analysis and Synthesis of Help-Desk Responses. KES (3) 2005: 890-897
57EESarah George, Ingrid Zukerman, Michael Niemann: Modeling Suppositions in Users' Arguments. User Modeling 2005: 19-29
56EEIngrid Zukerman, Christian Guttmann: Modeling Agents That Exhibit Variable Performance in a Collaborative Setting. User Modeling 2005: 210-219
55EEIngrid Zukerman: Argumentation Machines: New Frontiers in Argumentation and Computation edited by Chris ReedTimothy J. Norman. Computational Linguistics 31(1): 153-155 (2005)
54EESandra Carberry, Ingrid Zukerman: Preface to the Special Issue on Language-Based Interaction. User Model. User-Adapt. Interact. 15(1-2): 1-3 (2005)
53EEIngrid Zukerman, Sarah George: A Probabilistic Approach for Argument Interpretation. User Model. User-Adapt. Interact. 15(1-2): 5-53 (2005)
2004
52EEPawel Kowalczyk, Ingrid Zukerman, Michael Niemann: Analyzing the Effect of Query Class on Document Retrieval Performance. Australian Conference on Artificial Intelligence 2004: 550-561
51EEIngrid Zukerman, Michael Niemann, Sarah George: Improving the Presentation of Argument Interpretations Based on User Trials. Australian Conference on Artificial Intelligence 2004: 587-598
50EEChristian Guttmann, Ingrid Zukerman: Towards Models of Incomplete and Uncertain Knowledge of Collaborators' Internal Resources. MATES 2004: 58-72
49EESarah George, Ingrid Zukerman, Michael Niemann: An Anytime Algorithm for Interpreting Arguments. PRICAI 2004: 311-321
48EEYuval Marom, Ingrid Zukerman: Improving Newsgroup Clustering by Filtering Author-Specific Words. PRICAI 2004: 953-954
2003
47EESarah George, Ingrid Zukerman, Mark George: An information-theoretic approach for argument interpretation in a conversational setting. AAMAS 2003: 992-993
46EEIngrid Zukerman, Bhavani Raskutti, Yingying Wen: Query Expansion and Query Reduction in Document Retrieval. ICTAI 2003: 552-559
45EEIngrid Zukerman, Sarah George, Mark George: Incorporating a User Model into an Information Theoretic Framework for Argument Interpretation. User Modeling 2003: 106-116
2002
44EEIngrid Zukerman, Bhavani Raskutti, Yingying Wen: Experiments in Query Paraphrasing for Information Retrieval. Australian Joint Conference on Artificial Intelligence 2002: 24-35
43EESarah George, Ingrid Zukerman: Argument Interpretation Using Minimum Message Length. Australian Joint Conference on Artificial Intelligence 2002: 297-308
42EEIngrid Zukerman, Bhavani Raskutti: Lexical Query Paraphrasing for Document Retrieval. COLING 2002
41EEIngrid Zukerman, Sarah George: Towards a Noise-Tolerant, Representation-Independent Mechanism for Argument Interpretation. COLING 2002
40EEWerner Winiwarter, Ingrid Zukerman, Tsunenori Mine: Message from the NLIS Workshop Chairs. DEXA Workshops 2002: 201-204
2001
39EEIngrid Zukerman: An Integrated Approach for Generating Arguments and Rebuttals and Understanding Rejoinders. User Modeling 2001: 84-94
38 Ingrid Zukerman, Richard McConachy: Wishful: A Discourse Planning System That Considers a User's Inferences. Computational Intelligence 17(1): 1-61 (2001)
37EEIngrid Zukerman, Diane J. Litman: Natural Language Processing and User Modeling: Synergies and Limitations. User Model. User-Adapt. Interact. 11(1-2): 129-158 (2001)
36EEIngrid Zukerman, David W. Albrecht: Predictive Statistical Models for User Modeling. User Model. User-Adapt. Interact. 11(1-2): 5-18 (2001)
2000
35 Ingrid Zukerman, David W. Albrecht, Ann E. Nicholson, Krystyna Doktor: Trading Off Granularity against Complexity. PRICAI 2000: 241-251
34 Ingrid Zukerman, Nathalie Jitnah, Richard McConachy, Sarah George: Recognizing Intentions from Rejoinders in a Bayesian Interactive Argumentation System. PRICAI 2000: 252-263
1999
33 David W. Albrecht, Ingrid Zukerman, Ann E. Nicholson: Pre-sending Documents on the WWW: A Comparative Study. IJCAI 1999: 1274-1279
32 Ingrid Zukerman, Richard McConachy, Kevin B. Korb, Deborah Pickett: Exploratory Interaction with a Bayesian Argumentation System. IJCAI 1999: 1294-1299
31EEA. E. Bud, Ann E. Nicholson, Ingrid Zukerman, David W. Albrecht: A hybrid architecture for strategically complex imperfect information games. KES 1999: 42-45
30EERichard McConachy, Ingrid Zukerman: Dialogue Requirements for Argumentation Systems. Electron. Trans. Artif. Intell. 3(D): 89-124 (1999)
1998
29 Ingrid Zukerman, Richard McConachy, Kevin B. Korb: Bayesian Reasoning in an Abductive Mechanism for Argument Generation and Analysis. AAAI/IAAI 1998: 833-838
28 David W. Albrecht, Ann E. Nicholson, Ingrid Zukerman: Knowledge Acquisition for Goal Prediction in a Multi-user Adventure Game. PAKDD 1998: 1-12
27EEAnn E. Nicholson, Ingrid Zukerman, David W. Albrecht: A Decision-Theoretic Approach for Pre-sending Information on the WWW. PRICAI 1998: 575-586
26EEChristopher Leckie, Ingrid Zukerman: Inductive Learning of Search Control Rules for Planning. Artif. Intell. 101(1-2): 63-98 (1998)
25EEDavid 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)
1997
24EEIan Thomas, Ingrid Zukerman, Jonathan J. Oliver, David W. Albrecht, Bhavani Raskutti: Lexical Access for Speech Understanding using Minimum Message Length Encoding. UAI 1997: 464-471
23 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)
22EEBhavani Raskutti, Ingrid Zukerman: Generating queries and replies during information-seeking interactions. Int. J. Hum.-Comput. Stud. 47(6): 689-734 (1997)
1996
21 Yi Han, Ingrid Zukerman: Constraint Propagation in a Cooperative Approach for Multimodal Presentation Planning. ECAI 1996: 256-260
20 Richard McConachy, Ingrid Zukerman: Using Argument Graphs to Generate Arguments. ECAI 1996: 592-598
19EEIan Thomas, Ingrid Zukerman, Jonathan J. Oliver, Bhavani Raskutti: Lexical Access using Minimum Message Length Encoding. PRICAI 1996: 229-240
18EEBhavani Raskutti, Ingrid Zukerman: A Unified Approach to Handling Uncertainty during Cooperative Consultations. PRICAI 1996: 85-96
1995
17 Ingrid Zukerman, Richard McConachy: Generating Discourse across Several User Models: Maximizing Belief while Avoiding Boredom and Overload. IJCAI 1995: 1251-1259
16EEYi Han, Ingrid Zukerman: Using Cooperative Agents to Plan Multimodal Presentations. Multimodal Human-Computer Communication 1995: 122-157
1994
15 Bhavani Raskutti, Ingrid Zukerman: Acquisition of Information to Determine a User's Plan. ECAI 1994: 28-32
14 Ingrid Zukerman, Richard McConachy: Being Concise versus Being Shallow: Two Competing Discourse Planning Paradigms. ECAI 1994: 515-519
1993
13 Ingrid Zukerman, Richard McConachy: An Optimizing Method for Structuring Inferentially Linked Discourse. AAAI 1993: 202-207
12 Christopher Leckie, Ingrid Zukerman: An Inductive Approach to Learning Search Control Rules for Planning. IJCAI 1993: 1100-1105
11 Ingrid Zukerman, Richard McConachy: Generating Concise Discourse that Addresses a Users Inferences. IJCAI 1993: 1202-1207
10 Ingrid Zukerman, Richard McConachy: Consulting a User Model to Address a User's Inference during Content Planning. User Model. User-Adapt. Interact. 3(2): 155-185 (1993)
1991
9 Christopher Leckie, Ingrid Zukerman: Learning Search Control Rules for Planning: An Inductive Approach. ML 1991: 422-426
8EEBhavani Raskutti, Ingrid Zukerman: Handling Uncertainty During Plan Recognition in Task-Oriented Consultation Systems. UAI 1991: 308-315
7 Bhavani Raskutti, Ingrid Zukerman: Generation and Selection of Likely Interpretations during Plan Recognition in Task-Oriented Consultation Systems. User Model. User-Adapt. Interact. 1(3-4): 323-353 (1991)
1990
6 Ingrid Zukerman: A predictive approach for the generation of rhetorical devices. Computational Intelligence 6: 25-40 (1990)
1988
5EEIngrid Zukerman, Yee Han Cheong: Contradictions and Revisions as Explanatory Aids in the Delivery of Technical Information. Australian Joint Conference on Artificial Intelligence 1988: 124-139
4EELai Leng Hui, Ingrid Zukerman: Common-sense Resolution of Syntactic Ambiguity in Database Queries. Australian Joint Conference on Artificial Intelligence 1988: 396-409
3EEJonathan J. Oliver, Ingrid Zukerman: DISSOLVE: A System for the Generation of Human Oriented Solutions to Algebraic Equations. Australian Joint Conference on Artificial Intelligence 1988: 92-107
1987
2 Ingrid Zukerman: Goal-based Generation of Motivational Expressions in a Learning Environment. AAAI 1987: 327-333
1986
1 Ingrid Zukerman, Judea Pearl: Comprehension-Driven Generation of Meta-Technical Utterances in Math Tutoring. AAAI 1986: 606-611

Coauthor Index

1David W. Albrecht [24] [25] [27] [28] [31] [33] [35] [36] [67] [78]
2Timothy Baldwin [72] [76] [77]
3Shlomo Berkovsky [72] [76] [77]
4Fabian Bohnert [70] [72] [76] [79] [80]
5A. E. Bud [31]
6Sandra Carberry [54] [59] [60]
7Yee Han Cheong [5]
8Daniel Chester [59] [60]
9Seniz Demir [59] [60]
10Krystyna Doktor [35]
11Stephanie Elzer [59] [60]
12Mark George [45] [47]
13Sarah George [34] [41] [43] [45] [47] [49] [51] [53] [57] [63] [65] [66] [69] [74]
14Nancy Green [59] [60]
15Christian Guttmann [50] [56] [61]
16Yi Han [16] [21]
17Lai Leng Hui [4]
18Nathalie Japkowicz [71]
19Nathalie Jitnah [34]
20Kristiina Jokinen [23]
21Kevin B. Korb [29] [32]
22Pawel Kowalczyk [52]
23Christopher Leckie [9] [12] [26]
24Diane J. Litman [37]
25Enes Makalic [69] [73] [74] [75]
26Yuval Marom [48] [58] [62] [64] [65] [68] [71]
27Mark T. Maybury [23]
28Richard McConachy [10] [11] [13] [14] [17] [20] [29] [30] [32] [34] [38]
29Tsunenori Mine [40]
30Ann E. Nicholson [25] [27] [28] [31] [33] [35]
31Michael Niemann [49] [51] [52] [57] [63] [65] [66] [69] [73] [74] [75]
32Jonathan J. Oliver [3] [19] [24]
33Judea Pearl [1]
34Deborah Pickett [32]
35Bhavani Raskutti [7] [8] [15] [18] [19] [22] [24] [42] [44] [46]
36Daniel F. Schmidt [73] [78] [80]
37Liz Sonenberg [72] [76]
38Ian Thomas [19] [24]
39Keith Trnka [60]
40Yingying Wen [44] [46]
41Werner Winiwarter [40]
42Michael Zock [23]

Colors in the list of coauthors

Copyright © Tue Nov 3 08:52:44 2009 by Michael Ley (ley@uni-trier.de)