2759655
Cha-Cha: A System for Organizing Intranet Search Results
Although search over World Wide Web pages has recently received much academic and commercial attention, surprisingly little research has been done on how to search the web pages within large, diverse intranets. Intranets contain the information associated with the internal workings of an organization. 
 
A standard search engine retrieves web pages that fall within a widely diverse range of information contexts, but presents these results uniformly, in a ranked list. As an alternative, the Cha-Cha system organizes web search results in such a way as to reflect the underlying structure of the intranet. In our approach, an "outline" or "table of contents" is created by first recording the shortest paths in hyperlinks from root pages to every page within the web intranet. After the user issues a query, these shortest paths are dynamically combined to form a hierarchical outline of the context in which the search results occur. The system is designed to be helpful for users with a wide range of computer skills. Preliminary user study and survey results suggest that some users find the resulting structure more helpful than the standard retrieval results display for intranet search.
12964519
Development and evaluation of emerging design patterns for ubiquitous computing
Design patterns are a format for capturing and sharing design knowledge. In this paper, we look at a new domain for design patterns, namely ubiquitous computing. The overall goal of this work is to aid practice by speeding up the diffusion of new interaction techniques and evaluation results from researchers, presenting the information in a form more usable to practicing designers. Towards this end, we have developed an initial and emerging pattern language for ubiquitous computing, consisting of 45 pre-patterns describing application genres, physical-virtual spaces, interaction and systems techniques for managing privacy, and techniques for fluid interactions. We evaluated the effectiveness of our pre-patterns with 16 pairs of designers in helping them design location-enhanced applications. We observed that our pre-patterns helped new and experienced designers unfamiliar with ubiquitous computing in generating and communicating ideas, and in avoiding design problems early in the design process.
8944311
Recent shortcuts: using recent interactions to support shared activities
We present an empirical study of teams that revealed the amount of extraneous individual work needed to enable collaboration: finding references to other people, finding files to attach to email, managing incoming email attachments, managing the variety of files used in shared activities, and tracking what work is owed to others. Much of this work involves finding recently accessed objects that are needed again in the user's current task focus. These observations led to the design of Recent Shortcuts, a tool to help support coordination by making recently used objects easily accessible. Recent Shortcuts enables quick access to people (including groups of people), received attachments, files, and file folders that the user interacted with recently for re-use in the user's current context. Recent Shortcuts makes it easy to use these objects across applications with no additional user input and minimal changes to the user's applications or work practice. Early user experiences with a working prototype led to an extension that integrates recently accessed objects across multiple devices.
6272838
A visual language for sketching large and complex interactive designs
Informal, sketch-based design tools closely match the work practices of user interface designers. Current tools, however, are limited in the size and complexity of interaction that can be specified. We have created an advanced sketch-based visual language that allows for easy prototyping of large, complex interactive designs. In its current embodiment in the denim web design tool, the visual language allows designers to sketch reusable components for recurring page elements, such as navigation bars, as well as conditionals to illustrate and test transitions that depend on a user's input. Designers can also specify sites that accept richer user input than simple clicking. Our informal evaluation shows that these features allow designers with little programming experience to quickly create prototypes of large, complex web sites while still working inside an informal, sketch-based environment
8007626
DENIM: finding a tighter fit between tools and practice for Web site design
Through a study of web site design practice, we observed that web site designers design sites at different levels of refinement—site map, storyboard, and individual page—and that designers sketch at all levels during the early stages of design. However, existing web design tools do not support these tasks very well. Informed by these observations, we created DENIM, a system that helps web site designers in the early stages of design. DENIM supports sketching input, allows design at different refinement levels, and unifies the levels through zooming. We performed an informal evaluation with seven professional designers and found that they reacted positively to the concept and were interested in using such a system in their work.
5232648
Koala: capture, share, automate, personalize business processes on the web
We present Koala, a system that enables users to capture, share, automate, and personalize business processes on the web. Koala is a collaborative programming-by-demonstration system that records, edits, and plays back user interactions as pseudo-natural language scripts that are both human- and machine-interpretable. Unlike previous programming by demonstration systems, Koala leverages sloppy programming that interprets pseudo-natural language instructions (as opposed to formal syntactic statements) in the context of a given web page's elements and actions. Koala scripts are automatically stored in the Koalescence wiki, where a community of users can share, run, and collaboratively develop their "how-to" knowledge. Koala also takes advantage of corporate and personal data stores to automatically generalize and instantiate user-specific data, so that scripts created by one user are automatically personalized for others. Our initial experiences suggest that Koala is surprisingly effective at interpreting instructions originally written for people.
5082006
Mining motifs in massive time series databases
The problem of efficiently locating previously known patterns in a time series database (i.e., query by content) has received much attention and may now largely be regarded as a solved problem. However, from a knowledge discovery viewpoint, a more interesting problem is the enumeration of previously unknown, frequently occurring patterns. We call such patterns "motifs", because of their close analogy to their discrete counterparts in computation biology. An efficient motif discovery algorithm for time series would be useful as a tool for summarizing and visualizing massive time series databases. In addition it could be used as a subroutine in various other data mining tasks, including the discovery of association rules, clustering and classification. In this paper we carefully motivate, then introduce, a nontrivial definition of time series motifs. We propose an efficient algorithm to discover them, and we demonstrate the utility and efficiency of our approach on several real world datasets.
9391992
Web question answering: is more always better?
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.
7027901
Reliable Multicast Transport Protocol (RMTP)
This paper presents the design, implementation, and performance of a reliable multicast transport protocol (RMTP). The RMTP is based on a hierarchical structure in which receivers are grouped into local regions or domains and in each domain there is a special receiver called a designated receiver (DR) which is responsible for sending acknowledgments periodically to the sender, for processing acknowledgment from receivers in its domain, and for retransmitting lost packets to the corresponding receivers. Since lost packets are recovered by local retransmissions as opposed to retransmissions from the original sender, end-to-end latency is significantly reduced, and the overall throughput is improved as well. Also, since only the DRs send their acknowledgments to the sender, instead of all receivers sending their acknowledgments to the sender, a single acknowledgment is generated per local region, and this prevents acknowledgment implosion. Receivers in RMTP send their acknowledgments to the DRs periodically, thereby simplifying error recovery. In addition, lost packets are recovered by selective repeat retransmissions, leading to improved throughput at the cost of minimal additional buffering at the receivers. This paper also describes the implementation of RMTP and its performance on the Internet.
426181
Omnibase: Uniform Access to Heterogeneous Data for Question Answering
Although the World Wide Web contains a tremendous amount of information, the lack of uniform structure makes finding the right knowledge difficult. A solution is to turn the Web into a "virtual database" and to access it through natural language. We built Omnibase, a system that integrates heterogeneous data sources using an object-property-value model. With the help of Omnibase, our START natural language system can now access numerous heterogeneous data sources on the Web in a uniform manner, and answers millions of user questions with high precision.
13185193
Question answering from the web using knowledge annotation and knowledge mining techniques
We present a strategy for answering fact-based natural language questions that is guided by a characterization of real-world user queries. Our approach, implemented in a system called Aranea, extracts answers from the Web using two different techniques: knowledge annotation and knowledge mining. Knowledge annotation is an approach to answering large classes of frequently occurring questions by utilizing semi\-structured and structured Web sources. Knowledge mining is a statistical approach that leverages massive amounts of Web data to overcome many natural language processing challenges. We have integrated these two different paradigms into a question answering system capable of providing users with concise answers that directly address their information needs.