Publication statistics

Pub. period:1994-2011
Pub. count:29
Number of co-authors:37


Number of publications with 3 favourite co-authors:

Pedro Domingos:
Cody C. T. Kwok:
Corin R. Anderson:



Productive colleagues

Daniel S. Weld's 3 most productive colleagues in number of publications:

Mary Czerwinski:80
Jacob O. Wobbrock:71
Patrick Baudisch:57

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Daniel S. Weld

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University of Washington


Publications by Daniel S. Weld (bibliography)

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Weld, Daniel S., Mausam, A and Dai, Peng (2011): Execution control for crowdsourcing. In: Proceedings of the 2011 ACM Symposium on User Interface Software and Technology 2011. pp. 57-58.

Crowdsourcing marketplaces enable a wide range of applications, but constructing any new application is challenging -- usually requiring a complex, self-managing workflow in order to guarantee quality results. We report on the CLOWDER project, which uses machine learning to continually refine models of worker performance and task difficulty. We present decision-theoretic optimization techniques that can select the best parameters for a range of workflows. Initial experiments show our optimized workflows are significantly more economical than with manually set parameters.

© All rights reserved Weld et al. and/or ACM Press

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Gajos, Krzysztof Z., Weld, Daniel S. and Wobbrock, Jacob O. (2010): Automatically generating personalized user interfaces with Supple. In Artificial Intelligence, 174 (12) pp. 910-950.

Today's computer-human interfaces are typically designed with the assumption that they are going to be used by an able-bodied person, who is using a typical set of input and output devices, who has typical perceptual and cognitive abilities, and who is sitting in a stable, warm environment. Any deviation from these assumptions may drastically hamper the person's effectiveness-not because of any inherent barrier to interaction, but because of a mismatch between the person's effective abilities and the assumptions underlying the interface design. We argue that automatic personalized interface generation is a feasible and scalable solution to this challenge. We present our Supple system, which can automatically generate interfaces adapted to a person's devices, tasks, preferences, and abilities. In this paper we formally define interface generation as an optimization problem and demonstrate that, despite a large solution space (of up to 10^1^7 possible interfaces), the problem is computationally feasible. In fact, for a particular class of cost functions, Supple produces exact solutions in under a second for most cases, and in a little over a minute in the worst case encountered, thus enabling run-time generation of user interfaces. We further show how several different design criteria can be expressed in the cost function, enabling different kinds of personalization. We also demonstrate how this approach enables extensive user- and system-initiated run-time adaptations to the interfaces after they have been generated. Supple is not intended to replace human user interface designers-instead, it offers alternative user interfaces for those people whose devices, tasks, preferences, and abilities are not sufficiently addressed by the hand-crafted designs. Indeed, the results of our study show that, compared to manufacturers' defaults, interfaces automatically generated by Supple significantly improve speed, accuracy and satisfaction of people with motor impairments.

© All rights reserved Gajos et al. and/or Elsevier Science

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Hoffmann, Raphael, Amershi, Saleema, Patel, Kayur, Wu, Fei, Fogarty, James and Weld, Daniel S. (2009): Amplifying community content creation with mixed initiative information extraction. In: Proceedings of ACM CHI 2009 Conference on Human Factors in Computing Systems 2009. pp. 1849-1858.

Although existing work has explored both information extraction and community content creation, most research has focused on them in isolation. In contrast, we see the greatest leverage in the synergistic pairing of these methods as two interlocking feedback cycles. This paper explores the potential synergy promised if these cycles can be made to accelerate each other by exploiting the same edits to advance both community content creation and learning-based information extraction. We examine our proposed synergy in the context of Wikipedia infoboxes and the Kylin information extraction system. After developing and refining a set of interfaces to present the verification of Kylin extractions as a non primary task in the context of Wikipedia articles, we develop an innovative use of Web search advertising services to study people engaged in some other primary task. We demonstrate our proposed synergy by analyzing our deployment from two complementary perspectives: (1) we show we accelerate community content creation by using Kylin's information extraction to significantly increase the likelihood that a person visiting a Wikipedia article as a part of some other primary task will spontaneously choose to help improve the article's infobox, and (2) we show we accelerate information extraction by using contributions collected from people interacting with our designs to significantly improve Kylin's extraction performance.

© All rights reserved Hoffmann et al. and/or ACM Press

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Hoffmann, Raphael, Baudisch, Patrick and Weld, Daniel S. (2008): Evaluating visual cues for window switching on large screens. In: Proceedings of ACM CHI 2008 Conference on Human Factors in Computing Systems April 5-10, 2008. pp. 929-938.

An increasing number of users are adopting large, multi-monitor displays. The resulting setups cover such a broad viewing angle that users can no longer simultaneously perceive all parts of the screen. Changes outside the user's visual field often go unnoticed. As a result, users sometimes have trouble locating the active window, for example after switching focus. This paper surveys graphical cues designed to direct visual attention and adapts them to window switching. Visual cues include five types of frames and mask around the target window and four trails leading to the window. We report the results of two user studies. The first evaluates each cue in isolation. The second evaluates hybrid techniques created by combining the most successful candidates from the first study. The best cues were visually sparse -- combinations of curved frames which use color to pop-out and tapered trails with predictable origin.

© All rights reserved Hoffmann et al. and/or ACM Press

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Gajos, Krzysztof Z., Wobbrock, Jacob O. and Weld, Daniel S. (2008): Improving the performance of motor-impaired users with automatically-generated, ability-based interfaces. In: Proceedings of ACM CHI 2008 Conference on Human Factors in Computing Systems April 5-10, 2008. pp. 1257-1266.

We evaluate two systems for automatically generating personalized interfaces adapted to the individual motor capabilities of users with motor impairments. The first system, SUPPLE, adapts to users' capabilities indirectly by first using the ARNAULD preference elicitation engine to model a user's preferences regarding how he or she likes the interfaces to be created. The second system, SUPPLE++, models a user's motor abilities directly from a set of one-time motor performance tests. In a study comparing these approaches to baseline interfaces, participants with motor impairments were 26.4% faster using ability-based user interfaces generated by SUPPLE++. They also made 73% fewer errors, strongly preferred those interfaces to the manufacturers' defaults, and found them more efficient, easier to use, and much less physically tiring. These findings indicate that rather than requiring some users with motor impairments to adapt themselves to software using separate assistive technologies, software can now adapt itself to the capabilities of its users.

© All rights reserved Gajos et al. and/or ACM Press

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Gajos, Krzysztof Z., Everitt, Katherine, Tan, Desney S., Czerwinski, Mary and Weld, Daniel S. (2008): Predictability and accuracy in adaptive user interfaces. In: Proceedings of ACM CHI 2008 Conference on Human Factors in Computing Systems April 5-10, 2008. pp. 1271-1274.

While proponents of adaptive user interfaces tout potential performance gains, critics argue that adaptation's unpredictability may disorient users, causing more harm than good. We present a study that examines the relative effects of predictability and accuracy on the usability of adaptive UIs. Our results show that increasing predictability and accuracy led to strongly improved satisfaction. Increasing accuracy also resulted in improved performance and higher utilization of the adaptive interface. Contrary to our expectations, improvement in accuracy had a stronger effect on performance, utilization and some satisfaction ratings than the improvement in predictability.

© All rights reserved Gajos et al. and/or ACM Press

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Chen, Jiun-Hung and Weld, Daniel S. (2008): Recovering from errors during programming by demonstration. In: Proceedings of the 2008 International Conference on Intelligent User Interfaces 2008. pp. 159-168.

Many end-users wish to customize their applications, automating common tasks and routines. Unfortunately, this automation is difficult today -- users must choose between brittle macros and complex scripting languages. Programming by demonstration (PBD) offers a middle ground, allowing users to demonstrate a procedure multiple times and generalizing the requisite behavior with machine learning. Unfortunately, many PBD systems are almost as brittle as macro recorders, offering few ways for a user to control the learning process or correct the demonstrations used as training examples. This paper presents CHINLE, a system which automatically constructs PBD systems for applications based on their interface specification. The resulting PBD systems have novel interaction and visualization methods, which allow the user to easily monitor and guide the learning process, facilitating error recovery during training. CHINLE-constructed PBD systems learn procedures with conditionals and perform partial learning if the procedure is too complex to learn completely.

© All rights reserved Chen and Weld and/or ACM Press

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Wu, Fei and Weld, Daniel S. (2008): Automatically refining the wikipedia infobox ontology. In: Proceedings of the 2008 International Conference on the World Wide Web 2008. pp. 635-644.

The combined efforts of human volunteers have recently extracted numerous facts from Wikipedia, storing them as machine-harvestable object-attribute-value triples in Wikipedia infoboxes. Machine learning systems, such as Kylin, use these infoboxes as training data, accurately extracting even more semantic knowledge from natural language text. But in order to realize the full power of this information, it must be situated in a cleanly-structured ontology. This paper introduces KOG, an autonomous system for refining Wikipedia's infobox-class ontology towards this end. We cast the problem of ontology refinement as a machine learning problem and solve it using both SVMs and a more powerful joint-inference approach expressed in Markov Logic Networks. We present experiments demonstrating the superiority of the joint-inference approach and evaluating other aspects of our system. Using these techniques, we build a rich ontology, integrating Wikipedia's infobox-class schemata with WordNet. We demonstrate how the resulting ontology may be used to enhance Wikipedia with improved query processing and other features.

© All rights reserved Wu and Weld and/or ACM Press

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Adar, Eytan, Dontcheva, Mira, Fogarty, James and Weld, Daniel S. (2008): Zoetrope: interacting with the ephemeral web. In: Cousins, Steve B. and Beaudouin-Lafon, Michel (eds.) Proceedings of the 21st Annual ACM Symposium on User Interface Software and Technology October 19-22, 2008, Monterey, CA, USA. pp. 239-248.

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Etzioni, Oren, Banko, Michele, Soderland, Stephen and Weld, Daniel S. (2008): Open information extraction from the web. In Communications of the ACM, 51 (12) pp. 68-74.

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Adar, Eytan, Weld, Daniel S., Bershad, Brian N. and Gribble, Steven S. (2007): Why we search: visualizing and predicting user behavior. In: Proceedings of the 2007 International Conference on the World Wide Web 2007. pp. 161-170.

The aggregation and comparison of behavioral patterns on the WWW represent a tremendous opportunity for understanding past behaviors and predicting future behaviors. In this paper, we take a first step at achieving this goal. We present a large scale study correlating the behaviors of Internet users on multiple systems ranging in size from 27 million queries to 14 million blog posts to 20,000 news articles. We formalize a model for events in these time-varying datasets and study their correlation. We have created an interface for analyzing the datasets, which includes a novel visual artifact, the DTWRadar, for summarizing differences between time series. Using our tool we identify a number of behavioral properties that allow us to understand the predictive power of patterns of use.

© All rights reserved Adar et al. and/or International World Wide Web Conference Committee

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Hoffmann, Raphael, Fogarty, James and Weld, Daniel S. (2007): Assieme: finding and leveraging implicit references in a web search interface for programmers. In: Proceedings of the ACM Symposium on User Interface Software and Technology October 7-10, 2007, Newport, Rhode Island, USA. pp. 13-22.

Programmers regularly use search as part of the development process, attempting to identify an appropriate API for a problem, seeking more information about an API, and seeking samples that show how to use an API. However, neither general-purpose search engines nor existing code search engines currently fit their needs, in large part because the information programmers need is distributed across many pages. We present Assieme, a Web search interface that effectively supports common programming search tasks by combining information from Web-accessible Java Archive (JAR) files, API documentation, and pages that include explanatory text and sample code. Assieme uses a novel approach to finding and resolving implicit references to Java packages, types, and members within sample code on the Web. In a study of programmers performing searches related to common programming tasks, we show that programmers obtain better solutions, using fewer queries, in the same amount of time spent using a general Web search interface.

© All rights reserved Hoffmann et al. and/or ACM Press

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Gajos, Krzysztof Z., Wobbrock, Jacob O. and Weld, Daniel S. (2007): Automatically generating user interfaces adapted to users' motor and vision capabilities. In: Proceedings of the ACM Symposium on User Interface Software and Technology October 7-10, 2007, Newport, Rhode Island, USA. pp. 231-240.

Most of today's GUIs are designed for the typical, able-bodied user; atypical users are, for the most part, left to adapt as best they can, perhaps using specialized assistive technologies as an aid. In this paper, we present an alternative approach: SUPPLE++ automatically generates interfaces which are tailored to an individual's motor capabilities and can be easily adjusted to accommodate varying vision capabilities. SUPPLE++ models users. motor capabilities based on a onetime motor performance test and uses this model in an optimization process, generating a personalized interface. A preliminary study indicates that while there is still room for improvement, SUPPLE++ allowed one user to complete tasks that she could not perform using a standard interface, while for the remaining users it resulted in an average time savings

© All rights reserved Gajos et al. and/or ACM Press

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Wu, Fei and Weld, Daniel S. (2007): Autonomously semantifying wikipedia. In: Silva, Mario J., Laender, Alberto H. F., Baeza-Yates, Ricardo A., McGuinness, Deborah L., Olstad, Bjrn, Olsen, ystein Haug and Falco, Andr O. (eds.) Proceedings of the Sixteenth ACM Conference on Information and Knowledge Management - CIKM 2007 November 6-10, 2007, Lisbon, Portugal. pp. 41-50.

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Gajos, Krzysztof Z., Long, Jing Jing and Weld, Daniel S. (2006): Automatically generating custom user interfaces for users with physical disabilities. In: Eighth Annual ACM Conference on Assistive Technologies 2006. pp. 243-244.

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Gajos, Krzysztof Z., Czerwinski, Mary, Tan, Desney S. and Weld, Daniel S. (2006): Exploring the design space for adaptive graphical user interfaces. In: Celentano, Augusto (ed.) AVI 2006 - Proceedings of the working conference on Advanced visual interfaces May 23-26, 2006, Venezia, Italy. pp. 201-208.

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Gajos, Krzysztof and Weld, Daniel S. (2005): Preference elicitation for interface optimization. In: Proceedings of the 2005 ACM Symposium on User Interface Software and Technology 2005. pp. 173-182.

Decision-theoretic optimization is becoming a popular tool in the user interface community, but creating accurate cost (or utility) functions has become a bottleneck -- in most cases the numerous parameters of these functions are chosen manually, which is a tedious and error-prone process. This paper describes ARNAULD, a general interactive tool for eliciting user preferences concerning concrete outcomes and using this feedback to automatically learn a factored cost function. We empirically evaluate our machine learning algorithm and two automatic query generation approaches and report on an informal user study.

© All rights reserved Gajos and Weld and/or ACM Press

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Gajos, Krzysztof, Christianson, David B., Hoffmann, Raphael, Shaked, Tal, Henning, Kiera, Long, Jing Jing and Weld, Daniel S. (2005): Fast and Robust Interface Generation for Ubiquitous Applications. In: Beigl, Michael, Intille, Stephen S., Rekimoto, Jun and Tokuda, Hideyuki (eds.) UbiComp 2005 Ubiquitous Computing - 7th International Conference September 11-14, 2005, Tokyo, Japan. pp. 37-55.

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Gajos, Krzysztof and Weld, Daniel S. (2004): SUPPLE: automatically generating user interfaces. In: Nunes, Nuno Jardim and Rich, Charles (eds.) International Conference on Intelligent User Interfaces 2004 January 13-16, 2004, Funchal, Madeira, Portugal. pp. 93-100.

In order to give people ubiquitous access to software applications, device controllers, and Internet services, it will be necessary to automatically adapt user interfaces to the computational devices at hand (eg, cell phones, PDAs, touch panels, etc.). While previous researchers have proposed solutions to this problem, each has limitations. This paper proposes a novel solution based on treating interface adaptation as an optimization problem. When asked to render an interface on a specific device, our supple system searches for the rendition that meets the device's constraints and minimizes the estimated effort for the user's expected interface actions. We make several contributions: 1) precisely defining the interface rendition problem, 2) demonstrating how user traces can be used to customize interface rendering to particular user's usage pattern, 3) presenting an efficient interface rendering algorithm, 4) performing experiments that demonstrate the utility of our approach.

© All rights reserved Gajos and Weld and/or ACM Press

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Etzioni, Oren, Cafarella, Michael, Downey, Doug, Kok, Stanley, Popescu, Ana-Maria, Shaked, Tal, Soderland, Stephen, Weld, Daniel S. and Yates, Alexander (2004): Web-scale information extraction in knowitall: (preliminary results). In: Proceedings of the 2004 International Conference on the World Wide Web 2004. pp. 100-110.

Manually querying search engines in order to accumulate a large body of factual information is a tedious, error-prone process of piecemeal search. Search engines retrieve and rank potentially relevant documents for human perusal, but do not extract facts, assess confidence, or fuse information from multiple documents. This paper introduces KnowItAll, a system that aims to automate the tedious process of extracting large collections of facts from the web in an autonomous,domain-independent, and scalable manner. The paper describes preliminary experiments in which an instance of KnowItAll, running for four days on a single machine, was able to automatically extract 54,753 facts. KnowItAll associates a probability with each fact enabling it to trade off precision and recall. The paper analyzes KnowItAll's architecture and reports on lessons learned for the design of large-scale information extraction systems.

© All rights reserved Etzioni et al. and/or ACM Press

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Weld, Daniel S. (2003): What users want. In: Johnson, Lewis and Andre, Elisabeth (eds.) International Conference on Intelligent User Interfaces 2003 January 12-15, 2003, Miami, Florida, USA. p. 4.

Todays computer interfaces are one size fits all. Users with little programming experience have only limited opportunities to customize their interface to their task and work habits (e.g., adding buttons to a toolbar). Furthermore, the overhead induced by generic interfaces will be proportionately greater on small form-factor PDAs, embedded applications and wearable devices. Searching for a solution, researchers argue that productivity can be greatly enhanced if interfaces anticipated their users, adapted to their preferences, and reacted to high-level customization requests. But realizing these benefits is tricky, because there is an inherent tension between the dynamism implied by automatic interface adaptation and the stability required in order for the user to maintain an accurate mental model, predict the computers behavior, and feel in control. In this talk, I discuss several principles governing effective adaptation, describe algorithms for data mining user action traces, and suggest mechanisms for dynamically transforming interfaces.

© All rights reserved Weld and/or ACM Press

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Yates, Alexander, Etzioni, Oren and Weld, Daniel S. (2003): A reliable natural language interface to household appliances. In: Johnson, Lewis and Andre, Elisabeth (eds.) International Conference on Intelligent User Interfaces 2003 January 12-15, 2003, Miami, Florida, USA. pp. 189-196.

As household appliances grow in complexity and sophistication, they become harder and harder to use, particularly because of their tiny display screens and limited keyboards. This paper describes a strategy for building natural language interfaces to appliances that circumvents these problems. Our approach leverages decades of research on planning and natural language interfaces to databases by reducing the appliance problem to the database problem; the reduction provably maintains desirable properties of the database interface. The paper goes on to describe the implementation and evaluation of the EXACT interface to appliances, which is based on this reduction. EXACT maps each English user request to an SQL query, which is transformed to create a PDDL goal, and uses the Blackbox planner [13] to map the planning problem to a sequence of appliance commands that satisfy the original request. Both theoretical arguments and experimental evaluation show that EXACT is highly reliable.

© All rights reserved Yates et al. and/or ACM Press

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Lau, Tessa A., Domingos, Pedro and Weld, Daniel S. (2003): Learning programs from traces using version space algebra. In: Gennari, John H., Porter, Bruce W. and Gil, Yolanda (eds.) K-CAP 2003 - Proceedings of the 2nd International Conference on Knowledge Capture October 23-25, 2003, Sanibel Island, FL, USA. pp. 36-43.

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Kwok, Cody, Etzioni, Oren and Weld, Daniel S. (2001): Scaling question answering to the web. In ACM Transactions on Information Systems, 19 (3) pp. 242-262.

The wealth of information on the web makes it an attractive resource for seeking quick answers to simple, factual questions such as "who was the first American in space?" or "what is the second tallest mountain in the world?" Yet today's most advanced web search services (e.g., Google and AskJeeves) make it surprisingly tedious to locate answers to such questions. In this paper, we extend question-answering techniques, first studied in the information retrieval literature, to the web and experimentally evaluate their performance. First we introduce Mulder, which we believe to be the first general-purpose, fully-automated question-answering system available on the web. Second, we describe Mulder's architecture, which relies on multiple search-engine queries, natural-language parsing, and a novel voting procedure to yield reliable answers coupled with high recall. Finally, we compare Mulder's performance to that of Google and AskJeeves on questions drawn from the TREC-8 question answering track. We find that Mulder's recall is more than a factor of three higher than that of AskJeeves. In addition, we find that Google requires 6.6 times as much user effort to achieve the same level of recall as Mulder.

© All rights reserved Kwok et al. and/or ACM Press

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Kwok, Cody C. T., Etzioni, Oren and Weld, Daniel S. (2001): Scaling question answering to the Web. In: Proceedings of the 2001 International Conference on the World Wide Web 2001. pp. 150-161.

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Anderson, Corin R., Domingos, Pedro and Weld, Daniel S. (2001): Personalizing web sites for mobile users. In: Proceedings of the 2001 International Conference on the World Wide Web 2001. pp. 565-575.

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Lau, Tessa and Weld, Daniel S. (1999): Programming by Demonstration: An Inductive Learning Formulation. In: Maybury, Mark T. (ed.) International Conference on Intelligent User Interfaces 1999 January 5-8, 1999, Redondo Beach, California, USA. pp. 145-152.

Although Programming by Demonstration (PBD) has the potential to improve the productivity of unsophisticated users, previous PBD systems have used brittle, heuristic, domain-specific approaches to execution-trace generalization. In this paper we define two application-independent methods for performing generalization that are based on well-understood machine learning technology. TGENVS uses version-space generalization, and TGENFOIL is based on the FOIL inductive logic programming algorithm. We analyze each method both theoretically and empirically, arguing that TGENVS has lower sample complexity, but TGENFOIL can learn a much more interesting class of programs.

© All rights reserved Lau and Weld and/or ACM Press

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Lau, Tessa A., Etzioni, Oren and Weld, Daniel S. (1999): Privacy Interfaces for Information Management. In Communications of the ACM, 42 (10) pp. 88-94.

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Etzioni, Oren and Weld, Daniel S. (1994): A Softbot-Based Interface to the Internet. In Communications of the ACM, 37 (7) pp. 72-76.

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