We describe Analyza, a system that helps lay users explore data. Analyza has been used within two large real world systems. The first is a question-and-answer feature in a spreadsheet product. The second provides convenient access to a revenue/inventory database for a large sales force. Both user bases consist of users who do not necessarily have coding skills, demonstrating Analyza's ability to democratize access to data. We discuss the key design decisions in implementing this system. For instance, how to mix structured and natural language modalities, how to use conversation to disambiguate and simplify querying, how to rely on the ``semantics' of the data to compensate for the lack of syntactic structure, and how to efficiently curate the data.

We define a connection subgraph as a small subgraph of a large graph that best captures the relationship between two nodes. The primary motivation for this work is to provide a paradigm for exploration and knowledge discovery in large social networks graphs. We present a formal definition of this problem, and an ideal solution based on electricity analogues. We then show how to accelerate the computations, to produce approximate, but high-quality connection subgraphs in real time on very large (disk resident) graphs.We describe our operational prototype, and we demonstrate results on a social network graph derived from the World Wide Web. Our graph contains 15 million nodes and 96 million edges, and our system still produces quality responses within seconds.

The celebrated PageRank algorithm has proved to be a very effective paradigm for ranking results of web search algorithms. In this paper we refine this basic paradigm to take into account several evolving prominent features of the web, and propose several algorithmic innovations. First, we analyze features of the rapidly growing "frontier" of the web, namely the part of the web that crawlers are unable to cover for one reason or another. We analyze the effect of these pages and find it to be significant. We suggest ways to improve the quality of ranking by modeling the growing presence of "link rot" on the web as more sites and pages fall out of maintenance. Finally we suggest new methods of ranking that are motivated by the hierarchical structure of the web, are more efficient than PageRank, and may be more resistant to direct manipulation.

No abstract available.

The social impact from the World Wide Web cannot be underestimated, but technologies used to build the Web are also revolutionizing the sharing of business and government information within intranets. In many ways the lessons learned from the Internet carry over directly to intranets, but others do not apply. In particular, the social forces that guide the development of intranets are quite different, and the determination of a "good answer" for intranet search is quite different than on the Internet. In this paper we study the problem of intranet search. Our approach focuses on the use of rank aggregation, and allows us to examine the effects of different heuristics on ranking of search results.

Algorithmic tools for searching and mining the Web are becoming increasingly sophisticated and vital. In this context, algorithms that use and exploit structural information about the Web perform better than generic methods in both efficiency and reliability.We present an extensive characterization of the graph structure of the Web, with a view to enabling high-performance applications that make use of this structure. In particular, we show that the Web emerges as the outcome of a number of essentially independent stochastic processes that evolve at various scales. A striking consequence of this scale invariance is that the structure of the Web is "fractal"---cohesive subregions display the same characteristics as the Web at large. An understanding of this underlying fractal nature is therefore applicable to designing data services across multiple domains and scales.We describe potential applications of this line of research to optimized algorithm design for Web-scale data analysis.

This paper outlines the design of a web crawler implemented for IBM Almaden's WebFountain project and describes an optimization model for controlling the crawl strategy. This crawler is scalable and incremental. The model makes no assumptions about the statistical behaviour of web page changes, but rather uses an adaptive approachtomaintain data on actual change rates which are in turn used as inputs for the optimization. Computational results with simulated but realistic data show that there is no `magic bullet' - different, but equally plausible, objectives lead to conicting `optimal' strategies. However, we nd that there are compromise objectives which lead to good strategies that are robust against a number of criteria. Categories and Subject Descriptors H3.4 [Systems and Software]: Performance Evaluation (eciency and eectiveness); H4.3 [Communications Applications ]: Information Browsers; G1.6 [Optimization]: Nonlinear Programming General Terms Algorithms, Experimentation, Performance Keywords Crawler, incremental crawler, scalability, optimization # This work was completed while the author was on leaveat IBM Almaden Research Center. Copyright is held by the author/owner. WWW10, May 1-5, 2001, Hong Kong. ACM 1-58113-348-0/01/0005. 1.

Web pages may be organized, indexed, searched, and navigated along several different feature dimensions. We investigate different approaches to discovering geographic context for web pages, and describe a navigational tool for browsing web resources by geographic proximity.

This paper considers the problems of triangularizing and diagonalizing matrices over rings, with particular emphasis on the integral case. It begins with a description of fast algorithms for the computation of Hermite and Smith normal forms of integer matrices. Then it shows how to apply fast matrix multiplication techniques to the problem of triangularizing a matrix over a ring using elementary column operations. These general results lead to an algorithm for triangularizing integer matrices that has a faster running time than the known Hermite normal form algorithms. The triangular matrix that is computed has small entries like the Hermite normal form, and will suffice for many applications.

Review of: Nielsen, Jakob (ed.) (1989) Coordinating User Interfaces for Consistency, Academic Press, San Diego, CA. Reviewed by: Matthew J. Saltzman. Review of: Wolfram, Stephen (1988) Mathematica: A System for Doing Mathematics by Computer, Addison Wesley Publishing Co., Redwood City, CA. Reviewed by: Kevin S. McCurley. INFORMS Journal on Computing, ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.