5051372
Processing queries by linear constraints
The emergence of several new application domains for databases has introduced the need for more efficient complex query handling than databases currently support. These application domains include On-Line AnalyticaIProcessing(OLAP), Geographical Information Systems (GIS), and scientific databases. This paper focuses attention on a form of selection query, expressible in SQL but not evaluated efficiently by current DBMSs, with wide applicability in these new problem domains. We introduce a processing strategy for this class of queries, which we call queries by linear constraints (QBLC). This processing strategy can be implemented with a wide variety of multidimensional indexing structures that include the R-?&ee variants, the k-d-B-pee, the Buddy-Tree, and many more. Note that any processing strategy meant for general database use must guarantee that all correct auswers are returned. Therefore, all numerical techniques we employ uphold &is guarantee. Thus the most distinguishing characteristic of this processing strategy is its safe handling of numerical error (which can result in the dismissal of valid answers). This paper presents several theoretical results about our processing strategy, and the results of several experiments which show that the processing cost of selection queries by linear constraints can be reduced dramatically by using our processing strategy. ‘This work was partially supported by a David and Lucile Packard Foundation Fellowship in Science and Engineering, a Presidential Young Investigator Award, NASA Research Grant NAGW-3921, and OFtD grant 144ET33. . . ., Permission to make digital/hard copies of aIt or part of this mate&l for persons1 or classmom use is grsnted without fee provided thst the copies are not made or distributed for profit or commerckd advulbge, &e copyd&t notice, the title ofthe publication and its d&e appear, and notice is given that WPyright is by permission ofthe ACM, Inc. To copy othe-rwise, to republish tc~ post on servers or to redistribute to I&, requires specific pen&ion and/or fee PODS ‘ 97 Tucson Arizona IJSA ~pyri&t 1997 ACM O-89791-910-6/97/05 ..$xso Raghu Ramakrishnan Computer Sciences Department University of Wisconsin-Madison 1210 W. Dayton St., Madison, WI 53706
2449483
Client-Server Paradise
This paper describes the design and implementation of Paradise, a database system designed for handling GIS type of applications. The current version of Paradise, uses a client-server architecture and provides an extended-relational data model for modeling GIS applications. Paradise supports~an extended version of SQL and provides a graphical user interface for querying and browsing the database. We also describe the results of benchmarking Paradise using the Sequoia 2000 storage benchmark.
1840510
Evolution of a Controller with a Free Variable Using Genetic Programming
A mathematical formula containing one or more free variables is “general” in the sense that it provides a solution to an entire category of problems. For example, the familiar formula for solving a quadratic equation contains free variables representing the equation’s coefficients. Previous work has demonstrated that genetic programming can automatically synthesize the design for a controller consisting of a topological arrangement of signal processing blocks (such as integrators, differentiators, leads, lags, gains, adders, inverters, and multipliers), where each block is further specified (“tuned”) by a numerical component value, and where the evolved controller satisfies user-specified requirements. The question arises as to whether it is possible to use genetic programming to automatically create a “generalized” controller for an entire category of such controller design problems — instead of a single instance of the problem. This paper shows, for an illustrative problem, how genetic programming can be used to create the design for ‘both the topology and tuning of controller, where the controller contains a free variable.
5943191
Reliability measurement: from theory to practice
The gap between theory and practice of reliability measurement in software design is discussed, and key issues that underlie reliability measurement's evolution from theory to practice are presented. A panel discussion in which reliability measurement's salient issues, basic concepts, and underlying theory are outlined is included. Reliability measurement's role in the development life cycle is also discussed.<<ETX>>
7079167
Text classification without negative examples revisit
Traditionally, building a classifier requires two sets of examples: positive examples and negative examples. This paper studies the problem of building a text classifier using positive examples (P) and unlabeled examples (U). The unlabeled examples are mixed with both positive and negative examples. Since no negative example is given explicitly, the task of building a reliable text classifier becomes far more challenging. Simply treating all of the unlabeled examples as negative examples and building a classifier thereafter is undoubtedly a poor approach to tackling this problem. Generally speaking, most of the studies solved this problem by a two-step heuristic: first, extract negative examples (N) from U. Second, build a classifier based on P and N. Surprisingly, most studies did not try to extract positive examples from U. Intuitively, enlarging P by P' (positive examples extracted from U) and building a classifier thereafter should enhance the effectiveness of the classifier. Throughout our study, we find that extracting P' is very difficult. A document in U that possesses the features exhibited in P does not necessarily mean that it is a positive example, and vice versa. The very large size of and very high diversity in U also contribute to the difficulties of extracting P'. In this paper, we propose a labeling heuristic called PNLH to tackle this problem. PNLH aims at extracting high quality positive examples and negative examples from U and can be used on top of any existing classifiers. Extensive experiments based on several benchmarks are conducted. The results indicated that PNLH is highly feasible, especially in the situation where |P| is extremely small.
3420296
Parameter Free Bursty Events Detection in Text Streams
Text classification is a major data mining task. An advanced text classification technique is known as partially supervised text classification, which can build a text classifier using a small set of positive examples only. This leads to our curiosity whether it is possible to find a set of features that can be used to describe the positive examples. Therefore, users do not even need to specify a set of positive examples. As the first step, in this paper, we formalize it as a new problem, called hot bursty events detection, to detect bursty events from a text stream which is a sequence of chronologically ordered documents. Here, a bursty event is a set of bursty features, and is considered as a potential category to build a text classifier. It is important to know that the hot bursty events detection problem, we study in this paper, is different from TDT (topic detection and tracking) which attempts to cluster documents as events using clustering techniques. In other words, our focus is on detecting a set of bursty features for a bursty event. In this paper, we propose a new novel parameter free probabilistic approach, called feature-pivot clustering. Our main technique is to fully utilize the time information to determine a set of bursty features which may occur in different time windows. We detect bursty events based on the feature distributions. There is no need to tune or estimate any parameters. We conduct experiments using real life data, a major English newspaper Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the VLDB copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment. Proceedings of the 31st VLDB Conference, Trondheim, Norway, 2005 in Hong Kong, and show that the parameter free feature-pivot clustering approach can detect the bursty events with a high success rate.
1926620
Program Mapping onto Network Processors by Recursive Bipartitioning and Refining
Mapping packet processing applications onto embedded network processors (NP) is a challenging task due to the unique constraints of NP systems and the characteristics of network application domains. A remarkable difference with general multiprocessor task scheduling is that NPs are often programmed into a hybrid parallel and pipeline topology. In this paper, we introduce a multilevel balancing and refining algorithm for NP program mapping. We use a divide- and-conquer approach to recursively bipartition the task graph into disjoint subdomains. At each level of bipartition, the processing resources will be co-allocated so that an estimation of throughput can be derived. The bipartition continues until the code of the tasks can be fit into the instruction memory of processing elements. Then the algorithm iteratively refines the solution by migrating tasks from the bottleneck stage to other stages. The performance of our scheme is evaluated with a suite of NP benchmarks using SUIF/Machine SUIF compiler and Intel IXA Architecture Tool. The throughput improvement is significant: average throughput is increased by 20%, and the maximum is 108%.