46086053
Similarity Join Algorithms: An Introduction
A multi-function type sheet counting machine capable of counting sheets under a desired operational mode selected from a plurality of operational modes. As the sheets to be counted are deflected one after another away from a stack of sheets, electrical count pulses corresponding to the number of deflected sheets are generated, and a count corresponding to the number of generated pulses is stored in a counter. A reset circuit is provided so that, at the time of changing over to the add mode from any other operational mode, the counter is automatically reset to clear the count previously stored in the counter.
3251955
Containment join size estimation: models and methods
Recent years witnessed an increasing interest in researches in XML, partly due to the fact that XML has now become the de facto standard for data interchange over the internet. A large amount of work has been reported on XML storage models and query processing techniques. However, few works have addressed issues of XML query optimization. In this paper, we report our study on one of the challenges in XML query optimization: containment join size estimation. Containment join is well accepted as an important operation in XML query processing. Estimating the size of its results is no doubt essential to generate efficient XML query processing plans. We propose two models, the interval model and the position model, and a set of estimation methods based on these two models. Comprehensive performance studies were conducted. The results not only demonstrate the advantages of our new algorithms over existing algorithms, but also provide valuable insights into the tradeoff among various parameters.
2285434
Towards multidimensional subspace skyline analysis
The skyline operator is important for multicriteria decision-making applications. Although many recent studies developed efficient methods to compute skyline objects in a given space, none of them considers skylines in multiple subspaces simultaneously. More importantly, the fundamental problem on the semantics of skylines remains open: Why and in which subspaces is (or is not) an object in the skyline? Practically, users may also be interested in the skylines in any subspaces. Then, what is the relationship between the skylines in the subspaces and those in the super-spaces? How can we effectively analyze the subspace skylines? Can we efficiently compute skylines in various subspaces and answer various analytical queries?In this article, we tackle the problem of multidimensional subspace skyline computation and analysis. We explore skylines in subspaces. First, we propose the concept of Skycube, which consists of skylines of all possible nonempty subspaces of a given full space. Once a Skycube is materialized, any subspace skyline queries can be answered online. However, Skycube cannot fully address the semantic concerns and may contain redundant information. To tackle the problem, we introduce a novel notion of skyline group which essentially is a group of objects that coincide in the skylines of some subspaces. We identify the decisive subspaces that qualify skyline groups in the subspace skylines. The new notions concisely capture the semantics and the structures of skylines in various subspaces. Multidimensional roll-up and drill-down analysis is introduced. We also develop efficient algorithms to compute Skycube, skyline groups and their decisive subspaces. A systematic performance study using both real data sets and synthetic data sets is reported to evaluate our approach.
8670128
Top-k Set Similarity Joins
Similarity join is a useful primitive operation underlying many applications, such as near duplicate Web page detection, data integration, and pattern recognition. Traditional similarity joins require a user to specify a similarity threshold. In this paper, we study a variant of the similarity join, termed top-k set similarity join. It returns the top-k pairs of records ranked by their similarities, thus eliminating the guess work users have to perform when the similarity threshold is unknown before hand. An algorithm, topk-join, is proposed to answer top-k similarity join efficiently. It is based on the prefix filtering principle and employs tight upper bounding of similarity values of unseen pairs. Experimental results demonstrate the efficiency of the proposed algorithm on large-scale real datasets.
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.
47178135
Efficient similarity joins for near duplicate detection
With the increasing amount of data and the need to integrate data from multiple data sources, a challenging issue is to find near duplicate records efficiently. In this paper, we focus on efficient algorithms to find pairs of records such that their similarities are above a given threshold. Several existing algorithms rely on the prefix filtering principle to avoid computing similarity values for all possible pairs of records. We propose new filtering techniques by exploiting the ordering information; they are integrated into the existing methods and drastically reduce the candidate sizes and hence improve the efficiency. Experimental results show that our proposed algorithms can achieve up to 2.6x - 5x speed-up over previous algorithms on several real datasets and provide alternative solutions to the near duplicate Web page detection problem.
56789286
Dynamo: design, implementation, and evaluation of cooperative persistent object 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 persistent storage systems has become suboptimal for many computation/data intensive applications. In this paper, we introduce a revised architecture for persistent object management employing network attached storage: the dynamic object server environment (Dynamo). Dynamo introduces two main architectural innovations: (1) to provide high scalability, the object 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. Other systems have an a priori assignment of ‘object management’ functions to specific nodes; (2) Dynamo uses a cooperative cache management which employs a decentralized lottery-based page replacement strategy with a novel technique which attempts to put a page replaced from one node into the cache of another node which is likely to access the page in the near future. 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. Copyright © 2000 John Wiley & Sons, Ltd.
3544821
11,001 New Features for Statistical Machine Translation
We use the Margin Infused Relaxed Algorithm of Crammer et al. to add a large number of new features to two machine translation systems: the Hiero hierarchical phrase-based translation system and our syntax-based translation system. On a large-scale Chinese-English translation task, we obtain statistically significant improvements of +1.5 Bleu and + 1.1 Bleu, respectively. We analyze the impact of the new features and the performance of the learning algorithm.
37290278
cGridex: Efficient Processing of Continuous Range Queries over Moving Objects
In mobile computing environments, the continuous range query is one of the most important types of queries required to support various location-based services. With a large number of queries, the real-time response to query answers and the concurrent execution are two major challenges. In this paper, we propose a novel approach cGridex for efficient processing of continuous range queries over moving objects. cGridex abstracts the dynamic relations between moving objects and concurrent queries, and introduces the concept of coloring on a high level. With colored grids, it forms a direct mapping between moving objects and continuous queries, and can process both of them in a unified way, without redundant evaluation. By precomputing and materializing the color transferring relations, it avoids frequent operations between query sets and spatial join between objects and queries at each time interval, thus leading to fast query evaluation. The experimental results show that cGridex has good performance for the evaluation of continuous range queries.
2372115
PoClustering: Lossless Clustering of Dissimilarity Data
Given a set of objects V with a dissimilarity measure between pairs of objects in V , a PoCluster is a collection of sets P ⊂ powerset(V ) partially ordered by the ⊂ relation such that S ⊂ T iff the maximal dissimilarity among objects in S is less than the maximal dissimilarity among objects in T . PoClusters capture categorizations of objects that are not strictly hierarchical, such as those found in ontologies. PoClusters can not, in general, be constructed using hierarchical clustering algorithms. In this paper, we examine the relationship between PoClusters and dissimilarity matrices and prove that PoClusters are in one-to-one correspondence with the set of dissimilarity matrices. The PoClustering problem is NP-Complete, and we present a heuristic algorithm for it in this paper. Experiments on both synthetic and real datasets demonstrate the quality and scalability of the algorithms.
32582887
Novel Design and Fpga Implementation of Da-rns Fir Filters
Field programmable gate array (FPGA)-based digital signal processing has been widely used in multimedia applications. By combining distributed arithmetic (DA) and residue number system (RNS) in such designs, efficient area, speed and power efficiency can be achieved. In this paper, we propose novel techniques for the design and FPGA implementation of DA-RNS finite impulse response (FIR) filters. By introducing a novel low-cost moduli set and its selection method, efficient modulo arithmetic units inside the subfilters are designed. Then, a new residue-to-binary conversion algorithm, a so-called modified DA Chinese remainder theorem, is derived to reduce the modulo operations and provide an efficient residue-to-binary converter suitable to FPGA implementation. Based on these proposed techniques, a seventh-order DA-RNS FIR filter is designed, implemented and tested by using Xilinx FPGA tools. The implementation results show that the proposed filter design consumes only 77% of the power that the existing filter12,13 requires, while maintaining the same speed (throughput).