14820946
A hierarchical monothetic document clustering algorithm for summarization and browsing search results
Organizing Web search results into a hierarchy of topics and sub-topics facilitates browsing the collection and locating results of interest. In this paper, we propose a new hierarchical monothetic clustering algorithm to build a topic hierarchy for a collection of search results retrieved in response to a query. At every level of the hierarchy, the new algorithm progressively identifies topics in a way that maximizes the coverage while maintaining distinctiveness of the topics. We refer the proposed algorithm to as DisCover. Evaluating the quality of a topic hierarchy is a non-trivial task, the ultimate test being user judgment. We use several objective measures such as coverage and reach time for an empirical comparison of the proposed algorithm with two other monothetic clustering algorithms to demonstrate its superiority. Even though our algorithm is slightly more computationally intensive than one of the algorithms, it generates better hierarchies. Our user studies also show that the proposed algorithm is superior to the other algorithms as a summarizing and browsing tool.
27759262
Automatic categorization of web sites based on source types
An important issue with the Web is verification of the accuracy, currency and authenticity of the information associated with Web sites. One way to address this problem is to identify the "source" or "sponsor" of the Web site. However, source identification is non-trivial because the source of a Web site cannot always be determined by the URL or content of the site. In this paper, we propose a method for source identification that uses various types of inbound, outbound and internal interactions that arise due to hyperlinks between and within Web sites.
10991562
Strings: a high-performance distributed shared memory for symmetrical multiprocessor clusters
Introduces Strings, a high-performance distributed shared memory system designed for clusters of symmetrical multiprocessors (SMPs). The distinguishing feature of this system is the use of a fully multithreaded runtime system, written using POSIX threads. Strings also allows multiple application threads to be run on each node in a cluster. Since most modern UNIX systems can multiplex these threads on kernel-level lightweight processes, applications written using Strings can use all the processors in a SMP machine. This paper describes some of the architectural details of the system and analyzes the performance improvements with two example programs and a few benchmark programs from the SPLASH-2 suite.
14932066
On line predictive appearance-based tracking
We present a novel predictive statistical framework to improve the performance of an eigentracker. In addition, we use fast and efficient eigenspace updates to learn new views of the object being tracked on the fly. We also incorporate a new importance sampling mechanism which increases the robustness of the eigentracker and enables it to track nonconvex objects better. Our eigentracker is flexible-it is possible to use it symbolically with other trackers. We show its successful application in hand gesture analysis; and face and person tracking.
8794069
"Take One Get One Free": Leveraging P2P Networks for Content Promotion
The nature of digital content is undergoing a radical transformation due to the growing infusion of user-generated content. Users that generate content have a strong motivation to actively promote their content in order to achieve publicity, recognition or to simply spread their viewpoints, knowledge and creations. Existing content sharing mechanisms available to such users, such as in P2P file sharing, are pull-based, relegating the user to a passive role. To enable active participation from users, we propose Promoter, a framework that enhances P2P file sharing systems to support content promotion in addition to the available pull-based content search. Promotion is enabled by publicizing a user's content to peers and disseminating the content by incentivizing peers to download and further propagate it.
411400
Parity Problems in Planar Graphs
We consider the problem of counting the number of spanning trees in planar graphs. We prove tight bounds on the complexity of the problem, both in general and especially in the modular setting. We exhibit the problem to be complete for Logspace when the modulus is 2k, for constant k. On the other hand, we show that for any other modulus and in the non-modular case, our problem is as hard in the planar case as for the case of arbitrary graphs. This completely settles the question regarding the complexity of modular computation of the number of spanning trees in planar graphs. The techniques used rely heavily on algebraic-topology. In the spirit of counting problems modulo 2k, we also exhibit a highly parallel oplusL algorithm for finding the value of a Permanent modulo 2k. Previously, the best known result in this direction was Valiant's result that this problem lies in P.
6457662
ConvexFit: an optimal minimum-error convex fitting and smoothing algorithm with application to gate-sizing
Convex optimization has gained popularity due to its capability to reach global optimum in a reasonable amount of time. Convexity is often ensured by fitting the table data into analytically convex forms such as posynomials. However, fitting the look-up tables into the posynomial forms with minimum error itself may not be a convex optimization problem and hence excessive fitting errors may be introduced. In this paper, we propose to directly adjust the look-up table values into a numerically convex look-up table without explicit analytical form. We show that numerically "convexifying" the table data with minimum perturbation can be formulated as a convex semidefinite optimization problem and hence optimality can be reached in polynomial time. Without an explicit form limitation, we find that the fitting error is significantly reduced while the convexity is still ensured. As a result, convex optimization algorithms can still be applied. Furthermore, we also develop a "smoothing" algorithm to make the table data smooth and convex to facilitate the optimization process. Results from extensive experiments on industrial cell libraries demonstrate that our method reduces 30/spl times/ fitting error over a well-developed posynomial fitting algorithm. Its application to circuit tuning is also presented.