We present a new family of join algorithms, called ripple joins, for online processing of multi-table aggregation queries in a relational database management system (dbms). Such queries arise naturally in interactive exploratory decision-support applications. Traditional offline join algorithms are designed to minimize the time to completion of the query. In contrast, ripple joins are designed to minimize the time until an acceptably precise estimate of the query result is available, as measured by the length of a confidence interval. Ripple joins are adaptive, adjusting their behavior during processing in accordance with the statistical properties of the data. Ripple joins also permit the user to dynamically trade off the two key performance factors of online aggregation: the time between successive updates of the running aggregate, and the amount by which the confidence-interval length decreases at each update. We show how ripple joins can be implemented in an existing dbms using iterators, and we give an overview of the methods used to compute confidence intervals and to adaptively optimize the ripple join "aspect-ratio" parameters. In experiments with an initial implementation of our algorithms in the postgres dbms, the time required to produce reasonably precise online estimates was up to two orders of magnitude smaller than the time required for the best offline join algorithms to produce exact answers.

This paper presents a modified diary study that investigated how people performed personally motivated searches in their email, in their files, and on the Web. Although earlier studies of directed search focused on keyword search, most of the search behavior we observed did not involve keyword search. Instead of jumping directly to their

We describe the design, implementation, and pilot study for SenseMaker, an interface for information exploration across heterogeneous sources. We propose supporting the contextdriven evolution of a user's interests via: (1) an approximation of the current information context as the current collection of accumulated information references, and (2) a unified set of user-centered actions for examining the current context and for progressing from one context to the next. SenseMaker users examine their current context by experimenting iteratively with different organizing dimensions and levels of granularity for the current collection's display. They progress from one context to another by building upon, taking away from, or replacing the current collection. They can also return to a previous information context and continue exploring from there. Keywords Information exploration, digital libraries, information seeking, information retrieval INTRODUCTION The design of any interface must ...

We consider a variant of the view maintenance problem: How does one keep a materialized view up-to-date when the view definition itself changes? Can one do better than recomputing the view from the base relations? Traditional view maintenance tries to maintain the materialized view in response to modifications to the base relations; we try to “adapt ” the view in response to changes in the view definition. Such techniques are needed for applications where the user can change queries dynamically and see the changes in the results fast. Data archaeology, data visualization, and dynamic queries are examples of such applications. We consider all possible redefinitions of SQL SELECT-FROM-UHERE-GROUPBY, UNION, and EXCEPT views, and show how these views can be adapted using the old materialization for the cases where it is possible to do so. We identify extra information that can be kept with a materialization to facilitate redefinition. Multiple simultaneous changes to a view can be handled without necessarily materializing intermediate results. We iden-tify guidelines for users and database administrators that can be used to facilitate efficient view adaptation. 1

Understanding the extent to which people’s search behaviors differ in terms of the interaction flow and information targeted is important in designing interfaces to help World Wide Web users search more effectively. In this paper we describe a longitudinal log-based study that investigated variability in people’s interaction behavior when engaged in search-related activities on the Web. We analyze the search interactions of more than two thousand volunteer users over a five-month period, with the aim of characterizing differences in their interaction styles. The findings of our study suggest that there are dramatic differences in variability in key aspects of the interaction within and between users, and within and between the search queries they submit. Our findings also suggest two classes of extreme user – navigators and explorers – whose search interaction is highly consistent or highly variable. Lessons learned from these users can inform the design of tools to support effective Web-search interactions for everyone.

Human insight is crucial for extracting meaning out of massive data sets, yet current user interactions with databases don’t allow iterative, intuitive analysis. The Control project looks at ways to give users quicker, more direct interactivity with the data.

We present a novel Web search interaction feature which, for a given query, provides links to websites frequently visited by other users with similar information needs. These popular destinations complement traditional search results, allowing direct navigation to authoritative resources for the query topic. Destinations are identified using the history of search and browsing behavior of many users over an extended time period, whose collective behavior provides a basis for computing source authority. We describe a user study which compared the suggestion of destinations with the previously proposed suggestion of related queries, as well as with traditional, unaided Web search. Results show that search enhanced by destination suggestions outperforms other systems for exploratory tasks, with best performance obtained from mining past user behavior at query-level granularity.

Wireless sensor networks are an emerging area of research interest with a number of compelling potential applications. By architecting sensor networks as virtual databases, we can provide a well-understood nonprocedural programming interface suitable to data management, allowing the community to realize sensornet applications rapidly. We argue here that in order to achieve an energy-efficient and useful implementation, query processing operators should be implemented within the sensor network, and that approximate query results will play a key role. We observe that innetwork implementations of database operators require novel data-centric routing mechanisms, as well as a reconsideration of traditional network and database interface layering.

The aim of the work reported here was to better understand the usability issues raised when digital libraries are used in a natural setting. The method used was a protocol analysis of users working on a task of their own choosing to retrieve documents from publicly available digital libraries. Various classes of usability difficulties were found. Here, we focus on use in context --- that is, usability concerns that arise from the fact that libraries are accessed in particular ways, under technically and organisationally imposed constraints, and that use of any particular resource is discretionary. The concepts from an Interaction Framework, which provides support for reasoning about patterns of interaction between users and systems, are applied to understand interaction issues. Keywords Digital Libraries, video protocols, interaction modelling, HCI. 1.

The issue of how users can navigate their way through large information spaces is one that is crucial to the ever expanding and interlinking of computer systems. There are many ways of dealing with the issue of navigation. The use of appropriate metaphors is one, virtual reality and 3D interfaces another. A third is to provide adaptive interfaces based on individual differences in users navigational ability. This paper takes a critical look at the alternatives for assisting users to navigate information spaces and concludes by outlining a research agenda for navigation support.