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检索条件"任意字段=Conference on Space-Efficient Data Structures, Streams, and Algorithms"

共 743 条记录，以下是611-620 订阅

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algorithms for dynamic geometric problems over data streams

Algorithms for dynamic geometric problems over data streams

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Proceedings of the 36th Annual ACM Symposium on Theory of Computing

作者： Indyk, Piotr CSAIL MIT United States

The stream algorithms for dynamic geometric problems over data streams were analyzed. Low-storage data structures that maintain approximate solutions to geometric problems was presented. An algorithm for the bio-chromatic minimum weight matching problem was developed. Analysis shows that the algorithm can be implemented to use only O(log M) space when random bits required by H are not counted.

关键词： data structures

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Single-pass algorithms for mining frequency change patterns with limited space in evolving append-only and dynamic transaction data streams

Single-pass algorithms for mining frequency change patterns ...

引用

Proceedings - 2004 IEEE International conference on e-Technology, e-Commerce and e-Service, EEE 2004

作者： Li, Hua-Fu Lee, Suh-Yin Department of Computer Science National Chiao-Tung University Hisnchu Taiwan

ISBN: (纸本)0769520731

In this paper, we propose an online single-pass algorithm MFC-append (Mining Frequency Change patterns in append-only data streams) for online mining frequent frequency change items in continuous append-only data streams. An online space-efficient data structure called Change-Sketch is developed for providing fast response time to compute dynamic frequency changes between data streams. A modified approach MFC-dynamic (Mining Frequency Change patterns in dynamic data streams) is also presented to mine frequency changes in dynamic data streams. The theoretic analyses show that our algorithms meet the major performance requirements of single-pass, bounded storage, and real time for streaming data mining.

关键词： data mining

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Bulk operations for space-partitioning trees

Bulk operations for space-partitioning trees

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20th International conference on data Engineering

作者： Ghanem, TM Shah, R Mokbel, MF Aref, WG Vitter, JS Purdue Univ Dept Comp Sci W Lafayette IN 47907 USA

ISBN: (纸本)0769520650

The emergence of extensible index structures, e.g., GiST (Generalized Search Tree) [26] and SP-GiST (space-Partitioning Generalized Search Tree) [4], calls for a set of extensible algorithms to support different operations (e.g., insertion, deletion, and search). Extensible bulk operations (e.g., bulk loading and bulk insertion) are of the same importance and need to be supported in these index engines. In this paper we propose two extensible buffer-based algorithms for bulk operations in the class of space-partitioning trees;a class of hierarchical data structures that recursively decompose the space into disjoint partitions. The main idea of these algorithms is to build an in-memory tree of the target space-partitioning index. Then, data items are recursively partitioned into disk-based buffers using the in-memory tree. Although the second algorithm is designed for bulk insertion, it can be used in bulk loading as well. The proposed extensible algorithms are implemented inside SP-GiST;a framework for supporting the class of space-partitioning trees. Both algorithms have I/O bound O(NH/B), where N is the number of data items to be bulk loaded/inserted, B is the number of tree nodes that can fit in one disk page, H is the tree height in terms of pages after applying a clustering algorithm. Experimental results are provided to show the scalability and applicability of the proposed algorithms for the class of space-partitioning trees. A comparison of the two proposed algorithms shows that the first algorithm performs better in case of bulk loading. However the second algorithm is more general and can be used for efficient bulk insertion.

关键词： Trees (mathematics)

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Reversible sketches for efficient and accurate change detection over network data streams 04

Reversible sketches for efficient and accurate change detect...

引用

Proceedings of the 2004 ACM SIGCOMM Internet Measurement conference, IMC 2004

作者： Schweller, Robert Gupta, Ashish Parsons, Elliot Chen, Yan Department of Computer Science Northwestern University Evanston IL 60201-3150 United States

ISBN: (纸本)1581138210

Traffic anomalies such as failures and attacks are increasing in frequency and severity, and thus identifying them rapidly and accurately is critical for large network operators. The detection typically treats the traffic as a collection of flows and looks for heavy changes in traffic patterns (e.g., volume, number of connections). However, as link speeds and the number of flows increase, keeping per-flow state is not scalable. The recently proposed sketch-based schemes [14] are among the very few that can detect heavy changes and anomalies over massive data streams at network traffic speeds. However, sketches do not preserve the key (e.g., source IP address) of the flows. Hence, even if anomalies are detected, it is difficult to infer the culprit flows, making it a big practical hurdle for online deployment. Meanwhile, the number of keys is too large to record. To address this challenge, we propose efficient reversible hashing algorithms to infer the keys of culprit flows from sketches without storing any explicit key information. No extra memory or memory accesses are needed for recording the streaming data. Meanwhile, the heavy change detection daemon runs in the background with space complexity and computational time sublinear to the key space size. This short paper describes the conceptual framework of the reversible sketches, as well as some initial approaches for implementation. See [23] for the optimized algorithms in details. Evaluated with netflow traffic traces of a large edge router, we demonstrate that the reverse hashing can quickly infer the keys of culprit flows even for many changes with high accuracy. Copyright 2004 ACM.

关键词： Telecommunication networks

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DDS: An efficient dynamic dimension selection algorithm for nearest neighbor search in high dimensions

DDS: An efficient dynamic dimension selection algorithm for ...

引用

2004 IEEE International conference on Multimedia and Expo (ICME)

作者： Kuo, Chia-Chen Chen, Ming-Syan Electrical Engineering Department National Taiwan University Taipei Taiwan

ISBN: (纸本)0780386035

The Nearest Neighbor Search problem is defined as follows: given a set P of n points, answer queries for finding the closest point in P to the query point. This problem arises in a large variety of multimedia applications, particularly in the context of similarity search. In the past few years, there has been increasing interest in performing similarity search over high dimensional data especially for multimedia applications. Unfortunately, most well-known techniques for solving this problem suffer from the "curse of dimensionality" that means the performance of system scales poorly with increased dimensionality of underlying data. The refined algorithms typically achieve a query time that is logarithmic in the quantity of points and exponential in the number of dimensions. However, once the number of dimension exceeds 15, searching in k-d trees or related structures involves the examination of a large fraction of the search space, thereby performing no better than exhaustive search. In view of this, we propose an efficient dynamic dimension selection algorithm to improve the performance of the nearest neighbor search especially in high dimensions.

关键词： algorithms

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Single-pass algorithms for mining frequency change patterns with limited space in evolving append-only and dynamic transaction data streams

Single-pass algorithms for mining frequency change patterns ...

引用

IEEE International conference on e-Technology, e-Commerce and e-Service

作者： Hua-Fu Li Suh-Yin Lee Department of Computer Science and Information Engineering National Chiao Tung University Hsinchu Taiwan

ISBN: (纸本)0769520731

We propose an online single-pass algorithm MFC-append (mining frequency change patterns in append-only data streams) for online mining frequent frequency change items in continuous append-only data streams. An online space-efficient data structure called Change-Sketch is developed for providing fast response time to compute dynamic frequency changes between data streams. A modified approach MFC-dynamic (mining frequency change patterns in dynamic data streams) is also presented to mine frequency changes in dynamic data streams. The theoretic analyses show that our algorithms meet the major performance requirements of single-pass, bounded storage, and real time for streaming data mining.

关键词： Frequency data mining data structures Monitoring Decision trees Computer science data engineering Delay Performance analysis Algorithm design and analysis

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6th International conference on data Warehousing and Knowledge Discovery, DaWaK 2004

6th International Conference on Data Warehousing and Knowled...

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6th International conference on data Warehousing and Knowledge Discovery, DaWaK 2004

ISBN: (纸本)354022937X

The proceedings contain 39 papers. The special focus in this conference is on data Warehousing Design, Knowledge Discovery Framework and XML data Minig. The topics include: Conceptual design of XML document warehouses;bringing together partitioning, materialized views and indexes to optimize performance of relational data warehouses;a framework for guiding the design of geographical dimensional schemas;workload-based placement and join processing in node-partitioned data warehouses;novelty framework for knowledge discovery in databases;revisiting generic bases of association rules;mining maximal frequently changing subtree patterns from XML documents;discovering pattern-based dynamic structures from versions of unordered XML documents;space-efficient range-sum queries in OLAP;answering approximate range aggregate queries on OLAP data cubes with probabilistic guarantees;computing complex iceberg cubes by multiway aggregation and bounding;an aggregate-aware retargeting algorithm for multiple fact data warehouses;a partial pre-aggregation scheme for HOLAP engines;discovering multidimensional structure in relational data;inductive databases as ranking;inductive databases of polynomial equations;from temporal rules to temporal meta-rules;report from a knowledge exchange network;towards an adaptive approach for mining data streams in resource constrained environments;exploring possible adverse drug reactions by clustering event sequences;an algorithm for clustering data streams of categorical attributes;novel clustering approach that employs genetic algorithm with new representation scheme and multiple objectives;categorical data visualization and clustering using subjective factors;multidimensional data visual exploration by interactive information segments;metadata to support transformations and data & metadata lineage in a warehousing environment.

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Spatial approximation + sequential scan = efficient metric indexing

Spatial approximation + sequential scan = efficient metric i...

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XXIV International conference of the Chilean Computer Science Society, SCCC 2004

作者： Chávez, Edgar Herrera, Norma Reyes, Nora Escuela de Ciencias Físico-Matemáticas Universidad Michoacana Ciudad Universitaria Morelia Mich. Mexico Departamento de Informática Universidad National de San Luis Ejército de los Andes 950 San Luis Argentina

Proximity queries in metric spaces, or metric proximity queries for short, have instances suffering from the so-called "curse of dimensionality" referred to the apparent impossibility of beating the brute force approach (an exhaustive search to satisfy a metric proximity query). In other words, the cursed spaces resists indexing. Current research tends to alleviate this particular situation, since easy spaces can be indexed neatly. A recent hypothesis stablishes that it is just a fraction of the database which is resilient to indexing, and the proper approach would be to index each part separately. This is precisely the approach of this work. We use two different techniques for indexing complementary parts of a metric database. The Dynamic Spatial Approximation Tree (dsa-tree) is a recently proposed data structure for searching in metric spaces. It has been shown that it compares favorably against alternative data structures in spaces of high dimension or queries with low selectivity. On the other hand, pivot-based algorithms are effective tools for proximity searching in any metric spaces, if sufficient storage space is available. In this work we combine the concepts of spatial approximation and pivot-based algorithms. The new data structure maintains the full feature s of a dsa-tree while using the available memory to improve the query time. We show experimentally that our data structure is competitive choice for searching in cursed metric spaces. © 2004 IEEE.

关键词： Query languages

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An efficient index data structure with the capabilities of suffix trees and suffix arrays for alphabets of non-negligible size

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11th International conference on String Processing and Information Retrieval, SPIRE 2004

作者： Kim, Dong Kyue Jeon, Jeong Eun Park, Heejin School of Electrical and Computer Engineering Pusan National University Busan609-735 Korea Republic of College of Information and Communications Hanyang University Seoul133-791 Korea Republic of

ISBN: (纸本)9783540232100

The suffix tree and the suffix array are fundamental fulltext index data structures and many algorithms have been developed on them to solve problems occurring in string processing and information retrieval. Some problems are solved more efficiently using the suffix tree and others are solved more efficiently using the suffix array. We consider the index data structure with the capabilities of both the suffix tree and the suffix array without requiring much space. For the alphabets whose size is negligible, Abouelhoda et al. developed the enhance suffix array for this purpose. It consists of the suffix array and the child table. The child table stores the parent-child relationship between the nodes in the suffix tree so that every algorithm developed on the suffix tree can be run with a small and systematic modification. Since the child table consumes moderate space and is constructed very fast, the enhanced suffix array is almost as time/space-efficient as the suffix array. However, when the size of the alphabet is not negligible, the enhance suffix array loses the capabilities of the suffix tree. The pattern search in the enhanced suffix array takes O(m|Σ|) time where m is the length of the pattern and Σ is the alphabet, while the pattern search in the suffix tree takes O(m log |Σ|) time. In this paper, we improve the enhanced suffix array to have the capabilities of the suffix tree and the suffix array even when the size of the alphabet is not negligible. We do this by presenting a new child table, which improves the enhanced suffix array to support the pattern search in O(mlog |Σ|) time. Our index data structure is almost as time/spaceefficient as the enhanced suffix array. It consumes the same space as the enhanced suffix array and its construction time is slightly slower ( © Springer-Verlag Berlin Heidelberg 2004.

关键词： Trees (mathematics)

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A parallel algorithm based on search space partition for generating concepts

A parallel algorithm based on search space partition for gen...

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International conference on Parallel and Distributed Systems (ICPADS)

作者： Hong Qi Dayou Liu Chengquan Hu Ming Lu Liang Zhao College oc computer and Technology Jilin University Changchun China

ISBN: (纸本)0769521525

Concept lattice, the core data structure in formal concept analysis, has been used widely in machine learning, data mining and knowledge discovery, information retrieval, etc. The main difficulty with concept lattice-based system comes from the lattice construction itself. In this paper, a parallel algorithm based on the closure search space partition for computing concepts is proposed. This algorithm divides the closure search space into several subspaces in accordance with criterions prescribed ahead and introduces an efficient scheme to recognize the valid ones, in which the searching for closures is bounded. An intermediate structure is employed to judge the validity of a subspace and compute closures more efficiently. Since the searching in subspaces are independent tasks, a parallel algorithm based on search space partition can be directly reached.

关键词： Parallel algorithms Lattices data structures Information analysis Machine learning data mining Information retrieval Concurrent computing Machine learning algorithms Partitioning algorithms

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