Susan Dumais
Has also published under the name of:
"Susan T. Dumais" and "S. Dumais"
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Publications by Susan Dumais (bibliography)
» 2008 «
Adar, Eytan, Teevan, Jaime and Dumais, Susan (2008): Large scale analysis of web revisitation patterns. In: Proceedings of ACM CHI 2008 Conference on Human Factors in Computing Systems April 5-10, 2008. pp. 1197-1206. Available online
“Our work examines Web revisitation patterns. Everybody revisits Web pages, but their reasons for doing so can differ depending on the particular Web page, their topic of interest, and their intent. To characterize how people revisit Web content, we analyzed five weeks of Web interaction logs of over 612,000 users. We supplemented these findings by a survey intended to identify the intent behind the observed revisitation. Our analysis reveals four primary revisitation patterns, each with unique behavioral, content, and structural characteristics. Through our analysis we illustrate how understanding revisitation patterns can enable Web sites to provide improved navigation, Web browsers to predict users' destinations, and search engines to better support fast, fresh, and effective finding and re-finding.”
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White, Ryen W., Dumais, Susan and Teevan, Jaime (2008): How medical expertise influences web search interaction. In: Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2008. pp. 791-792. Available online
“Domain expertise can have an important influence on how people search. In this poster we present findings from a log-based study into how medical domain experts search the Web for information related to their expertise, as compared with non-experts. We find differences in sites visited, query vocabulary, and search behavior. The findings have implications for the automatic identification of domain experts from interaction logs, and the use of domain knowledge in applications such as query suggestion or page recommendation to support non-experts.”
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Barreau, Deborah, Capra, Robert, Dumais, Susan, Jones, William and Perez-Quinones, Manuel (2008): Introduction to keeping, refinding and sharing personal information. In ACM Transactions on Information Systems, 26 (4) p. 18
» 2007 «
Dumais, Susan (2007): Information retrieval in context. In: Proceedings of the 2007 International Conference on Intelligent User Interfaces 2007. p. 2. Available online
“Today's search engines return a wide range of information from diverse sources with lightening speed. The information that is returned, however, is independent of who asked the question or the context in which the information need arose. Next generation search engines will make increasing use of context about the searcher, domain and tasks to dramatically change the search landscape.”
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Leskovec, Jure, Dumais, Susan and Horvitz, Eric (2007): Web projections: learning from contextual subgraphs of the web. In: Proceedings of the 2007 International Conference on the World Wide Web 2007. pp. 471-480. Available online
“Graphical relationships among Web pages have been exploited in methods for ranking search results. To date, specific graphical properties have been used in these analyses. We introduce a Web Projection methodology that generalizes prior efforts of graphical relationships of the web in several ways. With the approach, we create subgraphs by projecting sets of pages and domains onto the larger web graph, and then use machine learning to construct predictive models that consider graphical properties as evidence. We describe the method and then present experiments that illustrate the construction of predictive models of search result quality and user query reformulation.”
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Clarke, Charles L. A., Agichtein, Eugene, Dumais, Susan and White, Ryen W. (2007): The influence of caption features on clickthrough patterns in web search. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2007. pp. 135-142. Available online
“Web search engines present lists of captions, comprising title, snippet, and URL, to help users decide which search results to visit. Understanding the influence of features of these captions on Web search behavior may help validate algorithms and guidelines for their improved generation. In this paper we develop a methodology to use clickthrough logs from a commercial search engine to study user behavior when interacting with search result captions. The findings of our study suggest that relatively simple caption features such as the presence of all terms query terms, the readability of the snippet, and the length of the URL shown in the caption, can significantly influence users' Web search behavior.”
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Teevan, Jaime, Dumais, Susan and Horvitz, Eric (2007): Characterizing the value of personalizing search. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2007. pp. 757-758. Available online
“We investigate the diverse goals that people have when they issue the same query to a search engine, and the ability of current search engines to address such diversity. We quantify the potential value of personalizing search results based on this analysis. Great variance was found in the results that different individuals rated as relevant for the same query -- even when the same information goal was expressed. Our analysis suggests that while search engines do a good job of ranking results to maximize global happiness, they do not do a very good job for specific individuals.”
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Downey, Doug, Dumais, Susan and Horvitz, Eric (2007): Heads and tails: studies of web search with common and rare queries. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2007. pp. 847-848. Available online
“A large fraction of queries submitted to Web search engines occur very infrequently. We describe search log studies aimed at elucidating behaviors associated with rare and common queries. We present several analyses and discuss research directions.”
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» 2006 «
Cutrell, Edward, Robbins, Daniel, Dumais, Susan and Sarin, Raman (2006): Fast, flexible filtering with phlat. In: Proceedings of ACM CHI 2006 Conference on Human Factors in Computing Systems 2006. pp. 261-270. Available online
“Systems for fast search of personal information are rapidly becoming ubiquitous. Such systems promise to dramatically improve personal information management, yet most are modeled on Web search in which users know very little about the content that they are searching. We describe the design and deployment of a system called Phlat that optimizes search for personal information with an intuitive interface that merges search and browsing through a variety of associative and contextual cues. In addition, Phlat supports a unified tagging (labeling) scheme for organizing personal content across storage systems (files, email, etc.). The system has been deployed to hundreds of employees within our organization. We report on both quantitative and qualitative aspects of system use. Phlat is available as a free download at http://research.microsoft.com/adapt/phlat/.”
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Agichtein, Eugene, Brill, Eric, Dumais, Susan and Ragno, Robert (2006): Learning user interaction models for predicting web search result preferences. In: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2006. pp. 3-10. Available online
“Evaluating user preferences of web search results is crucial for search engine development, deployment, and maintenance. We present a real-world study of modeling the behavior of web search users to predict web search result preferences. Accurate modeling and interpretation of user behavior has important applications to ranking, click spam detection, web search personalization, and other tasks. Our key insight to improving robustness of interpreting implicit feedback is to model query-dependent deviations from the expected "noisy" user behavior. We show that our model of clickthrough interpretation improves prediction accuracy over state-of-the-art clickthrough methods. We generalize our approach to model user behavior beyond clickthrough, which results in higher preference prediction accuracy than models based on clickthrough information alone. We report results of a large-scale experimental evaluation that show substantial improvements over published implicit feedback interpretation methods.”
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Agichtein, Eugene, Brill, Eric and Dumais, Susan (2006): Improving web search ranking by incorporating user behavior information. In: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2006. pp. 19-26. Available online
“We show that incorporating user behavior data can significantly improve ordering of top results in real web search setting. We examine alternatives for incorporating feedback into the ranking process and explore the contributions of user feedback compared to other common web search features. We report results of a large scale evaluation over 3,000 queries and 12 million user interactions with a popular web search engine. We show that incorporating implicit feedback can augment other features, improving the accuracy of a competitive web search ranking algorithms by as much as 31% relative to the original performance.”
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Radlinski, Filip and Dumais, Susan (2006): Improving personalized web search using result diversification. In: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2006. pp. 691-692. Available online
“We present and evaluate methods for diversifying search results to improve personalized web search. A common personalization approach involves reranking the top N search results such that documents likely to be preferred by the user are presented higher. The usefulness of reranking is limited in part by the number and diversity of results considered. We propose three methods to increase the diversity of the top results and evaluate the effectiveness of these methods.”
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» 2005 «
Fox, Steve, Karnawat, Kuldeep, Mydland, Mark, Dumais, Susan and White, Thomas (2005): Evaluating implicit measures to improve web search. In ACM Transactions on Information Systems, 23 (2) pp. 147-168
“In this article we describe an evaluation of relevance feedback (RF) algorithms using searcher simulations. Since these algorithms select additional terms for query modification based on inferences made from searcher interaction, not on relevance information searchers explicitly provide (as in traditional RF), we refer to them as implicit feedback models. We introduce six different models that base their decisions on the interactions of searchers and use different approaches to rank query modification terms. The aim of this article is to determine which of these models should be used to assist searchers in the systems we develop. To evaluate these models we used searcher simulations that afforded us more control over the experimental conditions than experiments with human subjects and allowed complex interaction to be modeled without the need for costly human experimentation. The simulation-based evaluation methodology measures how well the models learn the distribution of terms across relevant documents (i.e., learn what information is relevant) and how well they improve search effectiveness (i.e., create effective search queries). Our findings show that an implicit feedback model based on Jeffrey's rule of conditioning outperformed other models under investigation.”
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Teevan, Jaime, Dumais, Susan and Horvitz, Eric (2005): Personalizing search via automated analysis of interests and activities. In: Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2005. pp. 449-456. Available online
“We formulate and study search algorithms that consider a user's prior interactions with a wide variety of content to personalize that user's current Web search. Rather than relying on the unrealistic assumption that people will precisely specify their intent when searching, we pursue techniques that leverage implicit information about the user's interests. This information is used to re-rank Web search results within a relevance feedback framework. We explore rich models of user interests, built from both search-related information, such as previously issued queries and previously visited Web pages, and other information about the user such as documents and email the user has read and created. Our research suggests that rich representations of the user and the corpus are important for personalization, but that it is possible to approximate these representations and provide efficient client-side algorithms for personalizing search. We show that such personalization algorithms can significantly improve on current Web search.”
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Broder, Andrei Z., Maarek, Yoelle S., Bharat, Krishna, Dumais, Susan, Papa, Steve, Pedersen, Jan and Raghavan, Prabhakar (2005): Current trends in the integration of searching and browsing. In: Proceedings of the 2005 International Conference on the World Wide Web 2005. p. 793. Available online
“Searching and browsing are the two basic information discovery paradigms, since the early days of the Web. After more than ten years down the road, three schools seem to have emerged: (1) The search-centric school argues that guided navigation is superfluous since free form search has become so good and the search UI so common, that users can satisfy all their needs via simple queries (2) The taxonomy navigation school claims that users have difficulties expressing informational needs and (3) The meta-data centric school advocates the use of meta-data for narrowing large sets of results, and is successful in e-commerce where it is known as "multi faceted search". This panel brings together experts and advocates for all three schools, who will discuss these approaches and share their experiences in the field. We will ask the audience to challenge our experts with real information architecture problems.”
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Shen, Xuehua, Dumais, Susan and Horvitz, Eric (2005): Analysis of topic dynamics in web search. In: Proceedings of the 2005 International Conference on the World Wide Web 2005. pp. 1102-1103. Available online
“We report on a study of topic dynamics for pages visited by a sample of people using MSN Search. We examine the predictive accuracies of probabilistic models of topic transitions for individuals and groups of users. We explore temporal dynamics by comparing the accuracy of the models for predicting topic transitions at increasingly distant times in the future. Finally, we discuss directions for applying models of search topic dynamics.”
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» 2004 «
Paek, Tim, Dumais, Susan and Logan, Ron (2004): WaveLens: a new view onto Internet search results. In: Dykstra-Erickson, Elizabeth and Tscheligi, Manfred (eds.) Proceedings of ACM CHI 2004 Conference on Human Factors in Computing Systems April 24-29, 2004, Vienna, Austria. pp. 727-734. Available online
“Internet search results are typically displayed as a list conforming to a static style sheet. The difficulty of perusing this list can be exacerbated when screen real estate is limited. When space is limited, either, few results are seen, or result descriptions are abbreviated, making it difficult to know whether to follow a particular web link. In this paper, we describe "WaveLens," a dynamic layout technique for displaying search results, which addresses these issues by combining a fisheye lens with progressive exposure of page content. Results from a usability study showed that participants performed faster and more accurately on a search task with one of two distinct parameter settings of WaveLens as compared to the typical static list. In a post-hoc questionnaire, participants favored that setting over both the static list and another setting which involved animated zoom. We discuss design implications for the retrieval and display of search results.”
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Gabrilovich, Evgeniy, Dumais, Susan and Horvitz, Eric (2004): Newsjunkie: providing personalized newsfeeds via analysis of information novelty. In: Proceedings of the 2004 International Conference on the World Wide Web 2004. pp. 482-490. Available online
“We present a principled methodology for filtering news stories by formal measures of information novelty, and show how the techniques can be used to custom-tailor news feeds based on information that a user has already reviewed. We review methods for analyzing novelty and then describe Newsjunkie, a system that personalizes news for users by identifying the novelty of stories in the context of stories they have already reviewed. Newsjunkie employs novelty-analysis algorithms that represent articles as words and named entities. The algorithms analyze inter- and intra-document dynamics by considering how information evolves over time from article to article, as well as within individual articles. We review the results of a user study undertaken to gauge the value of the approach over legacy time-based review of newsfeeds, and also to compare the performance of alternate distance metrics that are used to estimate the dissimilarity between candidate new articles and sets of previously reviewed articles.”
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» 2003 «
Poltrock, Steven, Grudin, Jonathan, Dumais, Susan, Fidel, Raya, Bruce, Harry and Pejtersen, Annelise Mark (2003): Information seeking and sharing in design teams. In: Tremaine, Marilyn and Simone, Carla (eds.) Proceedings of the International ACM SIGGROUP Conference on Supporting Group Work 2003 November 9-12, 2003, Sanibel Island, Florida, USA. pp. 239-247. Available online
“Information retrieval is generally considered an individual activity, and information retrieval research and tools reflect this view. As digitally mediated communication and information sharing increase, collaborative information retrieval merits greater attention and support. We describe field studies of information gathering in two design teams that had very different products, disciplinary backgrounds, and tools. We found striking similarities in the kinds of information they sought and the methods used to get it. For example, each team sought information about design constraints from external sources. A common strategy was to propose ideas and request feedback, rather than to ask directly for recommendations. Some differences in information seeking and sharing reflected differences in work contexts. Our findings suggest some ways that existing team collaboration tools could support collaborative information retrieval more effectively.”
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Dumais, Susan, Cutrell, Edward, Cadiz, Jonathan J., Jancke, Gavin, Sarin, Raman and Robbins, Daniel C. (2003): Stuff I've seen: a system for personal information retrieval and re-use. In: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2003. pp. 72-79. Available online
“Most information retrieval technologies are designed to facilitate information discovery. However, much knowledge work involves finding and re-using previously seen information. We describe the design and evaluation of a system, called Stuff I've Seen (SIS), that facilitates information re-use. This is accomplished in two ways. First, the system provides a unified index of information that a person has seen, whether it was seen as email, web page, document, appointment, etc. Second, because the information has been seen before, rich contextual cues can be used in the search interface. The system has been used internally by more than 230 employees. We report on both qualitative and quantitative aspects of system use. Initial findings show that time and people are important retrieval cues. Users find information more easily using SIS, and use other search tools less frequently after installation.”
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Ringel, Meredith, Cutrell, Edward, Dumais, Susan and Horvitz, Eric (2003): Milestones in Time: The Value of Landmarks in Retrieving Information from Personal Stores. In: Proceedings of IFIP INTERACT03: Human-Computer Interaction 2003, Zurich, Switzerland. p. 184.
Jones, William, Bruce, Harry and Dumais, Susan (2003): How Do People Get Back to Information on the Web? How Can They Do It Better?. In: Proceedings of IFIP INTERACT03: Human-Computer Interaction 2003, Zurich, Switzerland. p. 793.
» 2002 «
Bennett, Paul N., Dumais, Susan and Horvitz, Eric (2002): Probabilistic combination of text classifiers using reliability indicators: models and results. In: Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2002. pp. 207-214. Available online
“The intuition that different text classifiers behave in qualitatively different ways has long motivated attempts to build a better metaclassifier via some combination of classifiers. We introduce a probabilistic method for combining classifiers that considers the context-sensitive reliabilities of contributing classifiers. The method harnesses reliability indicators -- variables that provide a valuable signal about the performance of classifiers in different situations. We provide background, present procedures for building metaclassifiers that take into consideration both reliability indicators and classifier outputs, and review a set of comparative studies undertaken to evaluate the methodology.”
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Dumais, Susan, Banko, Michele, Brill, Eric, Lin, Jimmy and Ng, Andrew (2002): Web question answering: is more always better?. In: Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2002. pp. 291-298. Available online
“This paper describes a question answering system that is designed to capitalize on the tremendous amount of data that is now available online. Most question answering systems use a wide variety of linguistic resources. We focus instead on the redundancy available in large corpora as an important resource. We use this redundancy to simplify the query rewrites that we need to use, and to support answer mining from returned snippets. Our system performs quite well given the simplicity of the techniques being utilized. Experimental results show that question answering accuracy can be greatly improved by analyzing more and more matching passages. Simple passage ranking and n-gram extraction techniques work well in our system making it efficient to use with many backend retrieval engines.”
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» 2001 «
Dumais, Susan, Cutrell, Edward and Chen, Hao (2001): Optimizing Search by Showing Results in Context. In: Beaudouin-Lafon, Michel and Jacob, Robert J. K. (eds.) Proceedings of the ACM CHI 2001 Human Factors in Computing Systems Conference March 31 - April 5, 2001, Seattle, Washington, USA. pp. 277-284. Available online
“We developed and evaluated seven interfaces for integrating semantic category information with Web search results. List interfaces were based on the familiar ranked-listing of search results, sometimes augmented with a category name for each result. Category interfaces also showed page titles and/or category names, but re-organized the search results so that items in the same category were grouped together visually. Our user studies show that all Category interfaces were more effective than List interfaces even when lists were augmented with category names for each result. The best category performance was obtained when both category names and individual page titles were presented. Either alone is better than a list presentation, but both together provide the most effective means for allowing users to quickly examining search results. These results provide a better understanding of the perceptual and cognitive factors underlying the advantage of category groupings and provide some practical guidance to Web search interface designers.”
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Jin, Rong and Dumais, Susan (2001): Probabilistic combination of content and links. In: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2001. pp. 402-403. Available online
“Previous research has shown that citations and hypertext links can be usefully combined with document content to improve retrieval. Links can be used in many ways, e.g., link topology can be used to identify important pages, anchor text can be used to augment the text of cited pages, and activation can be spread to linked pages. This paper introduces a probabilistic model that integrates content matching and these three uses of link information in a single unified framework. Experiments with a web collection show benefits for link information especially for general queries.”
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Dumais, Susan and Czerwinski, Mary (2001): Building Bridges from Theory to Practice. In: Proceedings of the Ninth International Conference on Human-Computer Interaction 2001. pp. 1358-1362.
Wenyin, L., Dumais, Susan, Sun, Y., Zhang, H., Czerwinski, Mary and Field, B. (2001): Semi-Automatic Image Annotation. In: Proceedings of IFIP INTERACT01: Human-Computer Interaction 2001, Tokyo, Japan. pp. 326-333.
» 2000 «
Chen, Hao and Dumais, Susan (2000): Bringing Order to the Web: Automatically Categorizing Search Results. In: Turner, Thea, Szwillus, Gerd, Czerwinski, Mary, Peterno, Fabio and Pemberton, Steven (eds.) Proceedings of the ACM CHI 2000 Human Factors in Computing Systems Conference April 1-6, 2000, The Hague, The Netherlands. pp. 145-152. Available online
“We developed a user interface that organizes Web search results into hierarchical categories. Text classification algorithms were used to automatically classify arbitrary search results into an existing category structure on-the-fly. A user study compared our new category interface with the typical ranked list interface of search results. The study showed that the category interface is superior both in objective and subjective measures. Subjects liked the category interface much better than the list interface, and they were 50% faster at finding information that was organized into categories. Organizing search results allows users to focus on items in categories of interest rather than having to browse through all the results sequentially.”
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Dumais, Susan and Chen, Hao (2000): Hierarchical Classification of Web Content. In: Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2000. pp. 256-263. Available online
» 1999 «
Czerwinski, Mary, Dumais, Susan, Robertson, George G., Dziadosz, Susan, Tiernan, Scott Lee and Dantzich, Maarten van (1999): Visualizing Implicit Queries for Information Management and Retrieval. In: Altom, Mark W. and Williams, Marian G. (eds.) Proceedings of the ACM CHI 99 Human Factors in Computing Systems Conference May 15-20, 1999, Pittsburgh, Pennsylvania. pp. 560-567. Available online
“In this paper, we describe the use of similarity metrics in a novel visual environment for storing and retrieving favorite web pages. The similarity metrics, called Implicit Queries, are used to automatically highlight stored web pages that are related to the currently selected web page. Two experiments explored how users manage their personal web information space with and without the Implicit Query highlighting and later retrieve their stored web pages. When storing and organizing web pages, users with Implicit Query highlighting generated slightly more categories. Implicit Queries also led to faster web page retrieval time, although the results were not statistically significant.”
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Durso, Francis T., Nickerson, Raymond S., Schvaneveldt, Roger W., Dumais, Susan, Lindsay, D. Stephen and Chi, Michelene T. H. (eds.) (1999): Handbook of Applied Cognition. John Wiley and Sons
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» 1995 «
Dumais, Susan (1995): What You Get Is What You Want: Combining Evidence for Effective Information Filtering. In: Proceedings of the Eighteenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 1995. p. 369. Available online
“Information filtering refers to the task of selecting objects of interest from an incoming stream of information. As part of NIST/ARPA's TREC Workshop, we used Latent Semantic Indexing (LSI) for filtering 336k documents from diverse sources (newswires, patents, newspapers, technical abstracts) for 50 topics of interest. We developed representations of user interests using two sources of information. A Word Filter used just the words in the topic statements. A RelDocs Filter used just relevant training documents and ignored the topic statement (a variant of relevance feedback). The RelDocs filter vector was 30% more effective than the detailed natural language description of interests. Combining these two vectors provided small additional improvements in filtering. On average, 7 of the top 10 documents are relevant using the combined vector method. Performance can further be improved by continually incorporating relevant test documents into the filter vector. Data combination of the Word and RelDocs retrieved sets was not generally successful in improving performance compared to the best individual method, although we believe it might be if additional sources are used. Both query and data combination methods are quite general and applicable to a variety of filtering applications.”
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» 1994 «
Adelson, Beth, Dumais, Susan and Olson, Judith S. (eds.) Proceedings of the ACM CHI 94 Human Factors in Computing Systems Conference April 24-28, 1994, Boston, Massachusetts.
Dumais, Susan, Belkin, Nicholas J., Borgman, Christine L. and Hancock-Beaulieu, Micheline (1994): Evaluating Interactive Retrieval Systems. In: Proceedings of the Seventeenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 1994. p. 361. Available online
“Most current information retrieval systems are highly interactive. Users ask queries, get immediate feedback, refine their queries, and so on. Methods for evaluating these dynamic systems have not kept pace with the rapid advances in system design. It is no longer enough to use the standard precision-recall measures to evaluate and to improve interactive retrieval systems. There is often no single final query to evaluate, with useful information being gathered from many different queries along the way. In addition, interfaces play a critical role in building effective retrieval systems. The best retrieval algorithm can be rendered functionally useless if the interface to it is unusable. Conversely, of course, the spiffiest new interface is not worth much without a good retrieval engine behind it. It would be easy if one could study interfaces and retrieval engines separately and take the best of both worlds. Unfortunately, there are important interactions that cannot be evaluated by studying components in isolation -- e.g., how do you incorporate ranking or relevance feedback for a Boolean retrieval engine, or how do you highlight matching terms if complex syntactic and semantic processing of queries is used? The design of effective interactive retrieval environments will require careful attention to the larger human - interface - retrieval-engine system. Systematic, generalizable evaluations of these larger interactive systems are possible both in the laboratory and in the field. The panelists will describe interactive retrieval experiments and experiences, focusing on: a) why it is important to study interactions b) how interactive retrieval performance should be measured, and c) how the methods for evaluation and findings generalize to other systems. Belkin will begin with an overview of some of the problems in evaluating interactive retrieval systems and will present a new framework characterizing IR as interaction with text. The remaining talks will describe end-user experiments involving highly interactive retrieval systems. The focus of these talks will be on the approaches, methods and instruments used to evaluate retrieval effectiveness and ease of use as well as the relationship between system functionality and the interface. Dumais will describe the importance of interfaces in retrieval, and will present examples of successful iterative interface design with the SuperBook and X-LSI systems. Hancock-Beaulieu will review a series of experiments on the Okapi system to systematically examine the effectiveness of different retrieval aids. Bergman will describe the multiple evaluation methods employed to study children's information-seeking behavior using the Science Library Catalog, a graphical browsing system supplemented by keyword searching tailored to children's skills, and attempts to generalize these evaluation methods to other IR environments.”
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» 1992 «
Dumais, Susan and Nielsen, Jakob (1992): Automating the Assignment of Submitted Manuscripts to Reviewers. In: Proceedings of the Fifteenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 1992. pp. 233-244. Available online
“The 117 manuscripts submitted for the Hypertext'91 conference were assigned to members of the review committee, using a variety of automated methods based on information retrieval principles and Latent Semantic Indexing. Fifteen reviewers provided exhaustive ratings for the submitted abstracts, indicating how well each abstract matched their interests. The automated methods do a fairly good job of assigning relevant papers for review, but they are still some what poorer than assignments made manually by human experts and substantially poorer than an assignment perfectly matching the reviewers' own ranking of the papers. A new automated assignment method called "n of 2n" achieves better performance than human experts by sending reviewers more papers than they actually have to review and then allowing them to choose part of their review load themselves.”
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» 1991 «
Angiolillo, Joel S., Marcus, Aaron, Casey, Steven M. and Dumais, Susan (1991): Designing Usable Documentation: New Directions for Human Factors. In: Proceedings of the Human Factors Society 35th Annual Meeting 1991. pp. 249-250.
“The Human Factors community has virtually ignored one of the most important components of the extended user interface, user documentation. Last year at the 34th Annual Meeting in Orlando there was only one paper on either the design or use of documentation. By comparison, there were approximately a hundred papers related to screen design for video display terminals. The same disparity shows up in the Human Factors Journal. Last year there were no papers on documentation and eleven on accessing information from video display terminals. This lack of research in the human factors of documentation is surprising for several reasons: First, documentation is ubiquitous and it is big business. Just about every software package and every piece of hardware comes with its own manual today. Second, the importance of documentation to the usability of a product is not a secret. Alphonse Chapanis, in his presidential address delivered at the Eighth Annual Meeting of the Human Factors Society, told the audience "A very large and important area of human factors engineering [has been] almost entirely neglected. This area consists of the language and the words that are attached to the tools, machines, systems, and operations with which we are concerned." Third, there is no shortage of interesting applied research questions in this area. To name a few: -- When and why do users turn to a manual? -- Does format affect perceived usability? How? -- How do people access information in a document? How can that access be made easier? -- How do technical writers create technical instructions? -- How can documentation be better integrated with online help and error support systems? Although all the participants on the panel have been actively studying the use of documentation, the focus of the panel will not be a recounting of past research. Rather the panelists will offer us direction, based on their extensive experience, for the next decade and beyond. Where are we going? What do we need to know so that we can build a science of documentation? Why have so many human factors practitioners shied away from documentation? How can we make significant improvements to the usability of documents? What form will the documentation of the year 2000 take, and how can human factors contribute to its usability?”
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Dumais, Susan and Schmitt, Deborah G. (1991): Iterative Searching in an Online Database. In: Proceedings of the Human Factors Society 35th Annual Meeting 1991. pp. 398-402.
“An experiment examined how people use an online retrieval system. Subjects solved general topical search problems using a database containing the full text of news articles (e.g., find articles about the "Background of the new prime minister of Great Britain"). Time, accuracy and content of the searches were recorded. Of particular interest was the use of two iterative search methods available in the interface -- a Lookup function that allowed users to explicitly specify an alternative query; and a LikeThese function that could be used to automatically generate a new query using articles the user marked as relevant. Results showed that subjects could easily use both query reformulation methods. Subjects generated much more effective LikeThese searches than Lookup searches. An analysis of individual subject differences suggests that the LikeThese method is more accessible to a wide range of users.”
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» 1990 «
Kraut, Robert E. and Dumais, Susan (1990): Computerization and the Quality of Working Life: The Role of Control. In: Lochovsky, Frederick H. and Allen, Robert (eds.) Proceedings of the Conference on Office Information Systems 1990 April 25-27, 1990, Cambridge, Massachusetts, USA. pp. 56-68.
“Does the degree of control people have over their work environments moderate the impact of computerization in organizations? This paper addresses this question with a quantitative case study and a national survey. Results of the case study show that clerical workers with more control over the day-to-day aspects of their jobs had better experiences with computing. However, the national sample provides no evidence to support the control hypothesis. In this study, women using computers had slightly worse jobs and more stress-related symptoms than those not using computers, and these negative associations with computerization weren't reduced if they had more control. It is likely that factors other than control had important impact on how computering technology was designed, deployed and used. Good design and good implementation, however they come about, may be more important that the users' control per se.”
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» 1988 «
Dumais, Susan, Furnas, George W., Landauer, Thomas K., Deerwester, Scott and Harshman, Richard (1988): Using Latent Semantic Analysis to Improve Access to Textual Information. In: Soloway, Elliot, Frye, Douglas and Sheppard, Sylvia B. (eds.) Proceedings of the ACM CHI 88 Human Factors in Computing Systems Conference June 15-19, 1988, Washington, DC, USA. pp. 281-285.
“This paper describes a new approach for dealing with the vocabulary problem in human-computer interaction. Most approaches to retrieving textual materials depend on a lexical match between words in users' requests and those in or assigned to database objects. Because of the tremendous diversity in the words people use to describe the same object, lexical matching methods are necessarily incomplete and imprecise. The latent semantic indexing approach tries to overcome these problems by automatically organizing text objects into a semantic structure more appropriate for matching user requests. This is done by taking advantage of implicit higher-order structure in the association of terms with text objects. The particular technique used in singular-value decomposition, in which a large term by text-object matrix is decomposed into a set of about 50 to 150 orthogonal factors from which the original matrix can be approximated by linear combination. Terms and objects are represented by 50 to 150 dimensional vectors and matched against user queries in this "semantic" space. Initial tests find this completely automatic method widely applicable and a promising way to improve users' access to many kinds of textual materials, or to objects and services for which textual descriptions are available.”
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Dumais, Susan, Kraut, Robert E. and Koch, Susan (1988): Computers' Impact on Productivity and Work Life. In: Allen, Robert (ed.) Proceedings of the Conference on Office Information Systems 1988 March 23-25, 1988, Palo Alto, California, USA. pp. 88-95.
“Rapid spread of computer and telecommunication technologies throughout white-collar work has forced researchers to consider their impacts on the people who use them. The present study uses a multi-method, lagged, time-series design to examine the impact of a computerized record system on the work life of customer service representatives in a large utility company. Results show that the computer technology had mixed effects in terms of both productivity and quality of working life, and that these effects varied depending on local organizational culture, management quality, type of worker and their detailed work tasks. Furthermore, during the year in which the computer system was being introduced, the computer system itself, its methods of use, and the managerial goals that spawned it all evolved in response to workers and other factors. These results are used to illustrate the conceptual and methodological complexities involved in establishing the causal impact of computer technology, and to suggest alternate methods for thinking about and measuring technological impact.”
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Furnas, George W., Deerwester, Scott, Dumais, Susan, Landauer, Thomas K., Harshman, Richard A., Streeter, Lynn A. and Lochbaum, Karen E. (1988): Information Retrieval using a Singular Value Decomposition Model of Latent Semantic Structure. In: Proceedings of the Eleventh Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 1988. pp. 465-480.
“In a new method for automatic indexing and retrieval, implicit higher-order structure in the association of terms with documents is modeled to improve estimates of term-document association, and therefore the detection of relevant documents on the basis of terms found in queries. Singular-value decomposition is used to decompose a large term by document matrix into 50 to 150 orthogonal factors from which the original matrix can be approximated by linear combination; both documents and terms are represented as vectors in a 50- to 150-dimensional space. Queries are represented as pseudo-documents vectors formed from weighted combinations of terms, and documents are ordered by their similarity to the query. Initial tests find this automatic method very promising.”
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» 1986 «
Jones, William P. and Dumais, Susan (1986): The Spatial Metaphor for User Interfaces: Experimental Tests of Reference by Location versus Name. In ACM Transactions on Information Systems, 4 (1) pp. 42-63
“The enduring dichotomy between spatial and symbolic modes of representation and retrieval acquires an added pragmatic dimension through recent developments in computer-based information retrieval. The standard name-based approach to object reference is now supplemented on some systems by a spatial alternative-often driven by an office or desktop metaphor. Little rigorous evidence is available, however, to support the supposition that spatial memory in itself is more effective than symbolic memory. The accuracy of spatial versus symbolic reference was assessed in three experiments. In Experiment 1 accuracy of location reference in a location-only filing condition was initially comparable to that in a name-only condition, but deteriorated much more rapidly with increases in the number of objects filled. In Experiment 2 subjects placed objects in a two-dimensional space containing landmarks (drawings of a desk, table, filing cabinets, etc.) designed to evoke an office metaphor, and in Experiment 3 subjects placed objects in an actual, three-dimensional mock office. Neither of these enhancements served to improve significantly the accuracy of location reference, and performance remained below that of a name-only condition in Experiment 1. The results raise questions about the utility of spatial metaphor over symbolic filing and highlight the need for continuing research in which considerations of technological and economic feasibility are balanced by considerations of psychological utility.”
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» 1985 «
Dumais, Susan and Jones, William P. (1985): A Comparison of Symbolic and Spatial Filing. In: Borman, Lorraine and Curtis, Bill (eds.) Proceedings of the ACM CHI 85 Human Factors in Computing Systems Conference April 14-18, 1985, San Francisco, California. pp. 127-130.
“The traditional and still dominant form of object reference in computing systems is symbolic - data files, programs, etc. are initially labeled and subsequently referred to by name. This approach is being supplemented on some systems by a spatial alternative which is often driven by an office or desktop metaphor (e.g. Apple's Lisa and Macintosh systems, or Bolt's 1979 Spatial Data Management System). In such systems, an object is placed in a simulated two- or three-dimensional space, and can later be retrieved by pointing to its location. In order to begin to understand the relative merits of spatial and symbolic filing schemes for representing and organizing information, we compared four ways of filing computer objects. We found location information to be of limited utility, either by itself or in combination with symbolic information. This calls into question the generality and efficacy of the desktop metaphor for information retrieval.”
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» 1983 «
Dumais, Susan and Landauer, Thomas K. (1983): Using Examples to Describe Categories. In: Smith, Raoul N., Pew, Richard W. and Janda, Ann (eds.) Proceedings of the ACM CHI 83 Human Factors in Computing Systems Conferenc December 12-15, 1983, Boston, Massachusetts, United States. pp. 112-115.
“The successful use of menu-based information retrieval system depends critically on users understanding the category names and partitions used by system designers. Some of the problems in this endeavor are psychological and have to do with naming large and ill-defined categories so that users can understand their contents, and effectively partitioning large sets of objects. Systems of interest (like home information systems) often consist of new and frequently changing content in large and varied domains, and are particularly prone to these problems. We explored several ways in which one might name categories in one such domain (Yellow Page category headings) - category names, category names plus examples, and examples alone. We found that three examples alone were essentially as good a way to name these categories as either an expertly chosen name or a name plus examples. Examples provide a promising possibility both as a means of flexibly naming menu categories and as a methodological tool to study certain categorization problems.”
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» 1982 «
Furnas, George W., Gomez, Louis M., Landauer, Thomas K. and Dumais, Susan (1982): Statistical Semantics: How Can a Computer Use What People Name Things to Guess What Things People Mean When They Name Things?. In: Nichols, Jean A. and Schneider, Michael L. (eds.) Proceedings of the SIGCHI conference on Human factors in computing systems March 15-17, 1982, Gaithersburg, Maryland, United States. pp. 251-253.
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Mar 19th, 2010
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