2987996
Mining patterns in long sequential data with noise
Pattern discovery in time series data has been a problem of great importance in many fields, e.g., computational biology, performance analysis, consumer behavior, etc. Recently, considerable amount of research has been carried out in this area. The facts that the input data is typically very large and noises may present in various formats pose great challenge to the mining process. Recently, we have made several new research advances in this area. In this paper, we present some of them. We will survey new models proposed to address different types of noises as well as scalable algorithms developed for efficiently mining patterns under each model.
14969897
Dynamic adaptive file management in a local area network
In light of advances in processor and networking technology, especially the emergence of network attached disks, the traditional client-server architecture of file systems has become suboptimal for many computation/data intensive applications. We introduce a revised architecture for file management employing network attached storage: the dynamic file server environment (Dynamo). Dynamo introduces two main architectural innovations: to provide high scalability, the file management functions are mainly performed cooperatively by the clients in the system. Furthermore, data is transferred directly to the client's cache from network-attached disks, thus avoiding copies from a disk to the server buffer and then over the network to the client. Secondly, Dynamo uses a cooperative cache management which employs a decentralized lottery-based page replacement strategy. We show via performance benchmarks run on the Dynamo system and simulation results how this architecture increases the system's adaptability, scalability and cost performance.
62615149
Mining Asynchronous Periodic Patterns in Time Series Data
Periodicy detection in time series data is a challenging problem of great importance in many applications. Most previous work focused on mining synchronous periodic patterns and did not recognize the misaligned presence of a pattern due to the intervention of random noise. In this paper, we propose a more flexible model of asynchronous periodic pattern that may be present only within a subsequence and whose occurrences may be shifted due to disturbance. Two parameters min/spl I.bar/rep and max/spl I.bar/dis are employed to specify the minimum number of repetitions that is required within each segment of nondisrupted pattern occurrences and the maximum allowed disturbance between any two successive valid segments. Upon satisfying these two requirements, the longest valid subsequence of a pattern is returned. A two-phase algorithm is devised to first generate potential periods by distance-based pruning followed by an iterative procedure to derive and validate candidate patterns and locate the longest valid subsequence. We also show that this algorithm cannot only provide linear time complexity with respect to the length of the sequence but also achieve space efficiency.
28890
Extension of Lower Probabilities and Coherence of Belief Measures
Coherence is an important concept which is introduced and discussed in a new mathematics branch, Imprecise Probability Theory. By using the Choquet integral, belief measures can be extended to be coherent lower previsions on the linear space consisting of all bounded functions. As a special case, we establish that all belief measures are coherent imprecise probabilities.
11841640
Accelerating Profile Queries in Elevation Maps
Elevation maps are a widely used spatial data representation in geographical information systems (GIS). Paths on elevation maps can be characterized by profiles, which describe relative elevation as a function of distance. In this research, we address the inverse of this mapping - given a profile, how to efficiently find paths that could have generated it. This is called the profile query problem. Profiles have a wide variety of uses that include registering tracking information, or even other maps, to a given map. We describe a probabilistic model to characterize the maximal likelihood that a point lying on a path matches the query profile. Propagation of such probabilities to neighboring points can effectively prune the search space. This model enables us to efficiently answer queries of arbitrary profiles with user-specified error tolerances. When compared to existing spatial index methods, our approach supports more flexible queries with orders of magnitude speedup.
19868872
Management Assistance for Work First via a Dynamic Website
The purpose of the Work First project is to assist the state Dept. of Health and Human Services (DHHS) staff and each county Dept. of Social Services (DSS) across the state in the management of welfare reform initiatives. Work First is the cash assistance program in NC. One important objective is to encourage and support program managers to use data on outcomes to assess their performance. This is accomplished by providing them with easy to use and easy to understand comprehensive information on the experiences of families and individuals that have received assistance through their agency over time.
3416923
Efficient Computation of the Skyline Cube
Skyline has been proposed as an important operator for multi-criteria decision making, data mining and visualization, and user-preference queries. In this paper. we consider the problem of efficiently computing a SKYCUBE, which consists of skylines of all possible non-empty subsets of a given set of dimensions. While existing skyline computation algorithms can be immediately extended to computing each skyline query independently, such "shared-nothing" algorithms are inefficient. We develop several computation sharing strategies based on effectively identifying the computation dependencies among multiple related skyline queries. Based on these sharing strategies, two novel algorithms, Bottom-Up and Top-Down algorithms, are proposed to compute SKYCUBE efficiently. Finally, our extensive performance evaluations confirm the effectiveness of the sharing strategies. It is shown that new algorithms significantly outperform the naive ones.
15242556
AFOPT: An Efficient Implementation of Pattern Growth Approach
In this paper, we revisit the frequent itemset mining (FIM) problem and focus on studying the pattern growth approach. Existing pattern growth algorithms differ in several dimensions: (1) item search order; (2) conditional database representation; (3) conditional database construction strategy; and (4) tree traversal strategy. They adopted different strategies on these dimensions. Several adaptive algorithms were proposed to try to find good strategies for general situations. In this paper, we described the implementation techniques of an adaptive pattern growth algorithm, called AFOPT, which demonstrated good performance on all tested datasets. We also extended the algorithm to mine closed and maximal frequent itemsets. Comprehensive experiments were conducted to demonstrate the efficiency of the proposed algorithms.
205873026
Control point adjustment for B-spline curve approximation
Pottmann et al. propose an iterative optimization scheme for approximating a target curve with a B-spline curve based on square distance minimization, or SDM. The main advantage of SDM is that it does not need a parameterization of data points on the target curve. Starting with an initial B-spline curve, this scheme makes an active B-spline curve converge faster towards the target curve and produces a better approximating B-spline curve than existing methods relying on data point parameterization. However, SDM is sensitive to the initial B-spline curve due to its local nature of optimization. To address this, we integrate SDM with procedures for automatically adjusting both the number and locations of the control points of the active spline curve. This leads to a method that is more robust and applicable than SDM used alone. Furthermore, it is observed that the most time consuming part of SDM is the repeated computation of the foot-point on the target curve of a sample point on the active B-spline curve. In our implementation, we speed up the foot-point computation by pre-computing the distance field of the target curve using the Fast Marching Method. Experimental examples are presented to demonstrate the effectiveness of our method. Problems for further research are discussed. q 2003 Elsevier Ltd. All rights reserved.
45794206
Rational Quadratic Parameterizations of Quadrics
Every irreducible quadric in E3 has infinitely many different rational quadratic parameterizations. These parameterizations and the relationships between them are investigated. It is shown that every faithful rational quadratic parameterization of a quadric can be generated by a stereographic projection from a point on the quadric, called the center of projection (COP). Two such parameterizations for the same quadric are related by a rational linear reparameterization if they have the same COP; otherwise they are related by a rational quadratic reparameterization. We also consider unfaithful parameterizations for which, in general, a one-to-one correspondence between points on the surface and parameters in the plane does not exist. It is shown that all unfaithful rational quadratic parameterizations of a properly degenerate quadric can be characterized by a simple canonical form, and there exist no unfaithful rational quadratic parameterizations for a nondegenerate quadric. In addition, given a faithful rational quadratic parameterization of a quadric, a new technique is presented to compute its base points and inversion formula. These results are applied to solve the problems of parameterizing the intersection of two quadrics and reparameterizing a given quadric parameterization with respect to a different COP without implicitization.
6017102
Database server workload characterization in an e-commerce environment
In an e-commerce system, the database server performance is crucial. A dynamic cache is often used to reduce the load on the database server, which reduces the need for scalability. A good understanding of the workload characteristics of the database server in an e-commerce environment is important to the design, tuning, and capacity planning of the database server. We characterize the database server workloads in a benchmark e-commerce system. We focus on the response time, CPU utilization, the database page reference characteristics, and disk I/Os of the database server. We find that using a dynamic cache can substantially reduce the CPU utilization but not always the number of disk I/Os of the database server. In most cases, using a dynamic cache reduces the temporal locality in database page references, but to a smaller degree than that reported in file servers and Web proxies. Interestingly, in certain e-commerce workloads, using a dynamic cache results in better temporal locality.