this article is that it demonstrates where novel focus# context views might become particularly useful for experienced users. It appears that novel, 3D interactive techniques might best be introduced alongside more familiar 2D visualizations, allowing the user to mix interaction strategies as necessary. The article by North and Shneiderman (2000) in this issue echoes this latter "nding

We have developed an in6 vative searchin terface that allowsnAOz5z ert users to move through large in97z86 tion spacesin a flexible manle without feelin lost. The design goal was to o#er users a "browsin the shelves" experien5 seamlessly in tegrated with focused search. Key to achievin our goal is the explicit exposure of hierarchical faceted metadatain a manz6 that is in tuitive an in vitin to users. After several iteration of design an testinA the usability results are strikinA] positive. We believe our approach marks a major step forward in search userin terfacesan can serve as a model for web-based collection of up to 100,000 items.

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.

We present a novel approach to visualize and explore unstructured text. The underlying technology, called TOPIC-O-GRAPHY TM , applies wavelet transforms to a custom digital signal constructed from words within a document. The resultant multiresolution wavelet energy is used to analyze the characteristics of the narrative flow in the frequency domain, such as theme changes, which is then related to the overall thematic content of the text document using statistical methods. The thematic characteristics of a document can be analyzed at varying degrees of detail, ranging from section-sized text partitions to partitions consisting of a few words. Using this technology, we are developing a visualization system prototype known as TOPIC ISLANDS TM to browse a document, generate fuzzy document outlines, summarize text by levels of detail and according to user interests, define meaningful subdocuments, query text content, and provide summaries of topic evolution. Keywords: text visualizati...

The enormous amount of information stored in unstructured texts cannot simply be used for further processing by computers, which typically handle text as simple sequences of character strings. Therefore, specific (pre-)processing methods and algorithms are required in order to extract useful patterns. Text mining refers generally to the process of extracting interesting information and knowledge from unstructured text. In this article, we discuss text mining as a young and interdisciplinary field in the intersection of the related areas information retrieval, machine learning, statistics, computational linguistics and especially data mining. We describe the main analysis tasks preprocessing, classification, clustering, information extraction and visualization. In addition, we briefly discuss a number of successful applications of text mining. 1

We revisit document clustering in the context of the Web. Specifically, we investigate on-line ephemeral clustering, whereby the input document set is generated dynamically, typically by search results, and the output clustering hierarchy has a short life span, and is used for interactive browsing purposes. Ephemeral clustering for interactive use introduces several new challenges. It requires an efficient algorithm, since clustering is performed on-line. It also requires high precision, because users who are not domain experts are less tolerant to errors, and because the resulting hierarchy is fully automatically generated, as opposed to off-line clustering in which the hierarchy is often manually modified. Finally, interactive clustering requires a presentation layer that enables users to effectively browse the hierarchy, including visualization techniques and automatic annotations of the hierarchy. We present new concepts, techniques and algorithms that tailor clustering to...

Simulation is an important tool in network protocol development, providing an effective way to perform controlled experiments, consider alternative designs, understand protocol interactions, and examine scales and topologies that are difficult to create in the laboratory. However, the scale and heterogeneity of today's networks create challenges for network simulation. In particular, configuring simulation inputs, properly modeling the myriad of interacting protocols, and processing and visualizing simulation output is becoming increasing difficult. The VINT project is developing a set of tools centered around ns simulator and nam network animator to meet these challenges. This paper describes the current status and future directions of this ongoing work. 1 Introduction The rapid diffusion of internetworking technology brings two major sources of stress to the underlying protocol mechanisms and associated design methods: scale and heterogeneity. Scale must be consid- This research ...

Abstract. An important problem for information access systems is that of organizing large sets of documents that have been retrieved in response to a query. Text categorization and text clustering are two natural language processing tasks whose results can be applied to document organization. This chapter describes user interfaces that use categories and clusters to organize retrieval results, and examines the relationship between the two. 1 1.

When search results against digital libraries and web resources have limited metadata, augmenting them with meaningful and stable category information can enable better overviews and support user exploration. This paper proposes six “fast-feature” techniques that use only features available in the search result list, such as title, snippet, and URL, to categorize results into meaningful categories. They use credible knowledge resources, including a US government organizational hierarchy, a thematic hierarchy from the Open Directory Project (ODP) web directory, and personal browse histories, to add valuable metadata to search results. In three tests the percent of results categorized for five representative queries was high enough to suggest practical benefits: general web search (76-90%), government web search (39-100%), and the Bureau of Labor Statistics website (48-94%). An additional test submitted 250 TREC queries to a search engine and successfully categorized 66 % of the top 100 using the ODP and 61 % of the top 350. Fast-feature techniques have been implemented in a prototype search engine. We propose research directions to improve categorization rates and make suggestions about how web site designers could re-organize their sites to support fast categorization of search results.

We describe four usability-enhancing interfaces to CITIDEL aimed at improving the user experience and supporting personalized information access by targeted communities. These comprise: a multimodal interaction facility with capability for out-of-turn input, interactive visualizations for exploratory analysis, a translation center exposing multilingual interfaces, as well as traditional usability enhancements. Pilot studies demonstrate the resulting improvements in quality, as measured across a number of metrics. Categories and Subject Descriptors H.5.2 [Information Interfaces and Presentation]: User