People often use more than one query when searching for information. They revisit search results to re-find information and build an understanding of their search need through iterative explorations of query formulation. These tasks are not well-supported by search interfaces and web browsers. We designed and built SearchPanel, a Chrome browser extension that supports people in their ongoing information seeking. This extension combines document and process metadata into an interactive representation of the retrieved documents that can be used for sense-making, navigation, and re-finding documents. In a real-world deployment spanning over two months, results show that SearchPanel appears to have been primarily used for complex information needs, in search sessions with long durations and high numbers of queries. When process metadata was present in the UI, searchers in explorative search sessions submitted more and longer queries and interacted more with the SERP. These results indicate that the process metadata features in SearchPanel seem to be of particular importance for exploratory search.

Although longer queries can produce better results for information seeking tasks, people tend to type short queries. We created an interface designed to encourage people to type longer queries, and evaluated it in two Mechanical Turk experiments. Results suggest that our interface manipulation may be effective for eliciting longer queries.

Exploratory search is a complex, iterative information seeking activity that involves running multiple queries and finding and examining many documents. We designed a query preview control that visualizes the distribution of newly-retrieved and re-retrieved documents prior to running the query. When evaluating the preview control with a control condition, we found effects on both people's information seeking behavior and improved retrieval performance. People spent more time formulating a query and were more likely to explore search results more deeply, retrieved a more diverse set of documents, and found more different relevant documents when using the preview.

Synchronous, explicit search has some interesting characteristics that distinguish it from other types of interaction: there is much more emphasis on interaction, as the system has to not only communicate search results to the user, but also mediate some forms of communication and data sharing among its users. There are new algorithms that need to be invented that use inputs from multiple people to produce search results, and new evaluation metrics need to be invented that reflect the collaborative and interactive nature of the task. Finally, we need to integrate the expertise of library and information science researchers and practitioners by revisiting real-world information seeking situations with an eye for explicit, synchronous collaborative search.

The Active Reading Application (ARA) brings the familiar experience of writing on paper to the tablet. The application augments paper-based practices with audio, the ability to review annotations, and sharing. It is designed to make it easier to review, annotate, and comment on documents by individuals and groups. ARA incorporates several patented technologies and draws on several years of research and experimentation.

Temporal aspects of documents can impact relevance for certain kinds of queries. In this paper, we build on earlier work of modeling temporal information. We propose an extension to the Query Likelihood Model that incorporates query-specific information to estimate rate parameters, and we introduce a temporal factor into language model smoothing and query expansion using pseudo-relevance feedback. We evaluate these extensions using a Twitter corpus and two newspaper article collections. Results suggest that, compared to prior approaches, our models are more effective at capturing the temporal variability of relevance associated with some topics.

The use of whiteboards is pervasive across a wide range of work domains. But some of the qualities that make them successful--an intuitive interface, physical working space, and easy erasure--inherently make them poor tools for archival and reuse. If whiteboard content could be made available in times and spaces beyond those supported by the whiteboard alone, how might it be appropriated? We explore this question via ReBoard, a system that automatically captures whiteboard images and makes them accessible through a novel set of user-centered access tools. Through the lens of a seven week workplace field study, we found that by enabling new workflows, ReBoard increased the value of whiteboard content for collaboration.

The modern workplace is inherently collaborative, and this collaboration relies on effective communication among co-workers. Many communication tools -- email, blogs, wikis, Twitter, etc. -- have become increasingly available and accepted in workplace communications. In this paper, we report on a study of communications technologies used over a one year period in a small US corporation. We found that participants used a large number of communication tools for different purposes, and that the introduction of new tools did not impact significantly the use of previously-adopted technologies. Further, we identified distinct classes of users based on patterns of tool use. This work has implications for the design of technology in the evolving ecology of communication tools.

Traditional interactive information retrieval systems function by creating inverted lists, or term indexes. For every term in the vocabulary, a list is created that contains the documents in which that term occurs and its relative frequency within each document. Retrieval algorithms then use these term frequencies alongside other collection statistics to identify the matching documents for a query. In this paper, we turn the process around: instead of indexing documents, we index query result sets. First, queries are run through a chosen retrieval system. For each query, the resulting document IDs are treated as terms and the score or rank of the document is used as the frequency statistic. An index of documents retrieved by basis queries is created. We call this index a reverted index. With reverted indexes, standard retrieval algorithms can retrieve the matching queries (as results) for a set of documents (used as queries). These recovered queries can then be used to identify additional documents, or to aid the user in query formulation, selection, and feedback.

In certain applications such as radiology and imagery analysis, it is important to minimize errors. In this paper we evaluate a structured inspection method that uses eye tracking information as a feedback mechanism to the image inspector. Our two-phase method starts with a free viewing phase during which gaze data is collected. During the next phase, we either segment the image, mask previously seen areas of the image, or combine the two techniques, and repeat the search. We compare the different methods proposed for the second search phase by evaluating the inspection method using true positive and false negative rates, and subjective workload. Results show that gaze-blocked configurations reduced the subjective workload, and that gaze-blocking without segmentation showed the largest increase in true positive identifications and the largest decrease in false negative identifications of previously unseen objects.

One of the core challenges now facing smart rooms is supporting realistic, everyday activities. While much research has been done to push forward the frontiers of novel interaction techniques, we argue that technology geared toward widespread adoption requires a design approach that emphasizes straightforward configuration and control, as well as flexibility. We examined the work practices of users of a large, multi-purpose conference room, and designed DICE, a system to help them use the room's capabilities. We describe the design process, and report findings about the system's usability and about people's use of a multi-purpose conference room.

We introduce the Ranked Feature Fusion framework for information retrieval system design. Typical information retrieval formalisms such as the vector space model, the best-match model and the language model first combine features (such as term frequency and document length) into a unified representation, and then use the representation to rank documents. We take the opposite approach: Documents are first ranked by the relevance of a single feature value and are assigned scores based on their relative ordering within the collection. A separate ranked list is created for every feature value and these lists are then fused to produce a final document scoring. This new "rank then combine" approach is extensively evaluated and is shown to be as effective as traditional "combine then rank" approaches. The model is easy to understand and contains fewer parameters than other approaches. Finally, the model is easy to extend (integration of new features is trivial) and modify. This advantage includes but is not limited to relevance feedback and distribution flattening.

We describe a new approach to information retrieval: algorithmic mediation for intentional, synchronous collaborative exploratory search. Using our system, two or more users with a common information need search together, simultaneously. The collaborative system provides tools, user interfaces and, most importantly, algorithmically-mediated retrieval to focus, enhance and augment the team's search and communication activities. Collaborative search outperformed post hoc merging of similarly instrumented single user runs. Algorithmic mediation improved both collaborative search (allowing a team of searchers to find relevant information more efficiently and effectively), and exploratory search (allowing the searchers to find relevant information that cannot be found while working individually).

Freeform digital ink annotation allows readers to interact with documents in an intuitive and familiar manner. Such marks are easy to manage on static documents, and provide a familiar annotation experience. In this paper, we describe an implementation of a freeform annotation system that accommodates dynamic document layout. The algorithm preserves the correct position of annotations when documents are viewed with different fonts or font sizes, with different aspect ratios, or on different devices. We explore a range of heuristics and algorithms required to handle common types of annotation, and conclude with a discussion of possible extensions to handle special kinds of annotations and changes to documents.

This paper presents a method for generating compact pictorial summarizations of video. We developed a novel approach for selecting still images from a video suitable for summarizing the video and for providing entry points into it. Images are laid out in a compact, visually pleasing display reminiscent of a comic book or Japanese manga. Users can explore the video by interacting with the presented summary. Links from each keyframe start video playback and/or present additional detail. Captions can be added to presentation frames to include commentary or descriptions such as the minutes of a recorded meeting. We conducted a study to compare variants of our summarization technique. The study participants judged the manga summary to be significantly better than the other two conditions with respect to their suitability for summaries and navigation, and their visual appeal.

Hitchcock is a system that allows users to easily create custom videos from raw video shot with a standard video camera.In contrast to other video editing systems, Hitchcock uses automatic analysis to determine the suitability of portions of the raw video.Unsuitable video typically has fast or erratic camera motion.Hitchcock first analyzes video to identify the type and amount of camera motion: fast pan, slow zoom, etc.Based on this analysis, a numerical "unsuitability" score is computed for each frame of the video.Combined with standard editing rules, this score is used to identify clips for inclusion in the final video and to select their start and end points.To create a custom video, the user drags keyframes corresponding to the desired clips into a storyboard.Users can lengthen or shorten the clip without specifying the start and end frames explicitly.Clip lengths are balanced automatically using a spring-based algorithm.

User interfaces for digital libraries tend to focus on retrieval: users retrieve documents online, but then print them out and work with them on paper.One reason for printing documents is to annotate them with freeform ink while reading.Annotation can help readers to understand documents and to make them their own.In addition, annotation can reveal readers' interests with respect to a particular document.In particular, it is possible to construct full-text queries based on annotated passages of documents.We describe an experiment that tested the effectiveness of such queries, as compared to relevance feedback query techniques.For a set of TREC topics and documents, queries derived from annotated passages produced significantly better results than queries derived from subjects' judgments of relevance.

Reading frequently involves not just looking at words on a page, but also underlining, highlighting and commenting, either on the text or in a separate notebook. This combination of reading with critical thinking and learning is called active reading [2]. To explore the premise that computation can enhance active reading we have built the XLibris “active reading machine.” XLibris uses a commercial high-resolution pen tablet display along with a paper-like user interface to support the key affordances of paper for active reading: the reader can hold a scanned image of a page in his lap and mark on it with digital ink. To go beyond paper, XLibris monitors the free-form ink annotations made while reading, and uses these to organize and to search for information. Readers can review, sort and filter clippings of their annotated text in a “Reader's Notebook.” XLibris also searches for material related to the annotated text, and displays links to similar documents unobtrusively in the margin. XLibris demonstrates that computers can help active readers organize and find information while retaining many of the advantages of reading on paper.

Hypertext interfaces are considered appropriate for information exploration tasks. The prohibitively expensive link creation effort, however, prevents traditional hypertext interfaces from being used with large coherent collections of text. Such collections typically require query--based interfaces. This paper examines a hybrid approach: the system described here creates anchors dynamically based on users' queries, and uses anchor selection as a query expansion mechanism. An experiment was conducted to compare browsing behavior in query-- and link--based interfaces. Results suggest that query--mediated links are as effective as explicit queries, and that strategies adopted by users affect performance. This work has implications for the design of information exploration interfaces; the dynamic link algorithms described here are being incorporated into a Web server.

Diagrams are data representations that convey information predominantly through combinations of graphical elements rather than through other channels such as text or interaction. We have implemented a prototype called AVE (Automatic Visualization Environment) that generates diagrams automatically based on a generative theory of diagram design. According to this theory, diagrams are constructed based on the data to be visualized rather than by selection from a predefined set of diagrams. This approach can be applied to knowledge represented by semantic networks. We give a brief introduction to the underlying theory, then describe the implementation and finally discuss strategies for extending the algorithm.

No abstract available.