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Andrew Y. Ng

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Publications by Andrew Y. Ng (bibliography)

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» 2006 «

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Brzozowski, Mike, Carattini, Kendra, Klemmer, Scott R., Mihelich, Patrick, Hu, Jiang and Ng, Andrew Y. (2006): groupTime: preference based group scheduling. In: Proceedings of ACM CHI 2006 Conference on Human Factors in Computing Systems 2006. pp. 1047-1056. Available online

As our business, academic, and personal lives continue to move at an ever-faster pace, finding times for busy people to meet has become an art. One of the most perplexing challenges facing groupware is effective asynchronous group scheduling (GS). This paper presents a lightweight interaction model for GS that can extend its reach beyond users of current group calendaring solutions. By expressing availability in terms of preferences, we create a flexible framework for GS that preserves plausible deniability while exerting social pressure to encourage honesty among users. We also propose an ontology that enables us to model user preferences with machine learning, predicting user responses to further lower cognitive load. The combination of visualization/direct manipulation with machine learning allows users to easily and efficiently optimize meeting times. We also suggest resulting design implications for this class of intelligent user interfaces.

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Minkov, Einat, Cohen, William W. and Ng, Andrew Y. (2006): Contextual search and name disambiguation in email using graphs. In: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2006. pp. 27-34. Available online

Similarity measures for text have historically been an important tool for solving information retrieval problems. In many interesting settings, however, documents are often closely connected to other documents, as well as other non-textual objects: for instance, email messages are connected to other messages via header information. In this paper we consider extended similarity metrics for documents and other objects embedded in graphs, facilitated via a lazy graph walk. We provide a detailed instantiation of this framework for email data, where content, social networks and a timeline are integrated in a structural graph. The suggested framework is evaluated for two email-related problems: disambiguating names in email documents, and threading. We show that reranking schemes based on the graph-walk similarity measures often outperform baseline methods, and that further improvements can be obtained by use of appropriate learning methods.

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» 2001 «

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Ng, Andrew Y., Zheng, Alice X. and Jordan, Michael I. (2001): Stable algorithms for link analysis. In: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2001. pp. 258-266. Available online

The Kleinberg HITS and the Google PageRank algorithms are eigenvector methods for identifying ``authoritative'' or ``influential'' articles, given hyperlink or citation information. That such algorithms should give reliable or consistent answers is surely a desideratum, and in [10], we analyzed when they can be expected to give stable rankings under small perturbations to the linkage patterns. In this paper, we extend the analysis and show how it gives insight into ways of designing stable link analysis methods. This in turn motivates two new algorithms, whose performance we study empirically using citation data and web hyperlink data.

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Changes to this page (author)

21 Feb 2010: Enabled abstracts to be shown on Andrew Y. Ng's author page.
24 Jun 2007: Author was edited
24 Jun 2007: Author was edited
19 Jun 2007: Author was added to the bibliography

Publication statistics

Publication period:2001-2006
Publication count:3
Number of co-authors:9



Productive colleagues

Andrew Y. Ng's 3 most productive colleagues in number of publications:

Scott R. Klemmer:26
William W. Cohen:11
Michael I. Jordan:4


Collaboration count

Number of publications with 3 favourite co-authors:

Michael I. Jordan:1
Einat Minkov:1
William W. Cohen:1

 

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Mar 20

Computer programs emerge as the outcome of complex human processes of cognition, communication and negotiation, which serve to establish the meaningful embedding of the computer system in its intended use context.

-- Floyd, 1992, p. 24

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