54110472
Fast and Accurate Text Classification via Multiple Linear Discriminant Projections
Publisher Summary 
Text classification is a standard problem in information retrieval (IR). A learner is presented with training documents, each labeled as containing or not containing material relevant to a given topic. Support vector machines (SVMs) have shown superb performance for text classification tasks. They are accurate, robust, and quick to apply to test instances. Their only potential drawback is their training time and memory requirement. SVMs have been trained on data sets with several thousand instances, but Web directories today contain millions of instances that are valuable for mapping billions of Web pages into Yahoo!-like directories. This chapter presents Simple Iterative Multiple Projection on Lines (SIMPL), a nearly linear-time classification algorithm that mimics the strengths of SVMs while avoiding the training bottleneck. It uses Fisher's linear discriminant, a classical tool from statistical pattern recognition, to project training instances to a carefully selected low-dimensional subspace before inducing a decision tree on the projected instances. SIMPL uses efficient sequential scans and sorts, and is comparable in speed and memory scalability to widely used naive Bayes (NB) classifiers, but it beats NB accuracy decisively.
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.
9807325
A Fast Algorithm for Point Labeling Problem
In the map labeling problem, we are given a set P = {p1, p2, . . . , pn} of point sites distributed on a 2D map. The label of a point pi is an axis-parallel rectangle of specified size. The objective is to label maximum number of points on the map so that the placed labels are mutually non-overlapping. Here, we investigate a special class of map labeling problem where (i) the height of the label of each point is the same but its length may be different from the others, (ii) the label of a point pi touches the point at one of its four corners and (iii) it does not obscure any other point in P . We describe an efficient heuristic algorithm for this problem which runs in O(n √ n) time in the worst case. We run our algorithm as well as the algorithm proposed in [14] on the available benchmarks [13]. The results produced by our algorithm is same as that of [14] in most of the cases, and is one less in few cases. But the time taken by our algorithm is much less than [14].
30169882
Aspect graph construction with noisy feature detectors
Many three-dimensional (3D) object recognition strategies use aspect graphs to represent objects in the model base. A crucial factor in the success of these object recognition strategies is the accurate construction of the aspect graph, its ease of creation, and the extent to which it can represent all views of the object for a given setup. Factors such as noise and nonadaptive thresholds may introduce errors in the feature detection process. This paper presents a characterization of errors in aspect graphs, as well as an algorithm for estimating aspect graphs, given noisy sensor data. We present extensive results of our strategies applied on a reasonably complex experimental set, and demonstrate applications to a robust 3D object recognition problem.
2052039
Overlay Node Placement: Analysis, Algorithms and Impact on Applications
Overlay routing has emerged as a promising approach to improving performance and reliability of Internet paths. To fully realize the potential of overlay routing under the constraints of deployment costs in terms of hardware, network connectivity and human effort, it is critical to carefully place infrastructure overlay nodes to balance the trade-off between performance and resource constraints. In this paper, we investigate approaches to perform intelligent placement of overlay nodes to facilitate (i) resilient routing and (ii) TCP performance improvement. We formulate objective functions to accurately capture application behavior: reliability and TCP performance, and develop several placement algorithms, which offer a wide range of trade-offs in complexity and required knowledge of the client- server location and traffic load. Using simulations on synthetic and real Internet topologies, and PlanetLab experiments, we demonstrate the effectiveness of the placement algorithms and objective functions developed, respectively. We conclude that an approach, hybrid of random and greedy approaches, provides the best tradeoff between computational efficiency and accuracy. We also uncover the fundamental challenge in simultaneously optimizing for reliability and TCP performance, and propose a simple unified algorithm to achieve the same.
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.
6539802
Robot localization using uncalibrated camera invariants
We describe a set of image measurements which are invariant to the camera internals but are location variant. We show that using these measurements it is possible to calculate the self-localization of a robot using known landmarks and uncalibrated cameras. We also show that it is possible to compute, using uncalibrated cameras, the Euclidean structure of 3-D world points using multiple views from known positions. We are free to alter the internal parameters of the camera during these operations. Our initial experiments demonstrate the applicability of the method.