452018
Online event-driven subsequence matching over financial data streams
Subsequence similarity matching in time series databases is an important research area for many applications. This paper presents a new approximate approach for automatic online subsequence similarity matching over massive data streams. With a simultaneous on-line segmentation and pruning algorithm over the incoming stream, the resulting piecewise linear representation of the data stream features high sensitivity and accuracy. The similarity definition is based on a permutation followed by a metric distance function, which provides the similarity search with flexibility, sensitivity and scalability. Also, the metric-based indexing methods can be applied for speed-up. To reduce the system burden, the event-driven similarity search is performed only when there is a potential event. The query sequence is the most recent subsequence of piecewise data representation of the incoming stream which is automatically generated by the system. The retrieved results can be analyzed in different ways according to the requirements of specific applications. This paper discusses an application for future data movement prediction based on statistical information. Experiments on real stock data are performed. The correctness of trend predictions is used to evaluate the performance of subsequence similarity matching.
10114115
The Optimal-Location Query
We propose and solve the optimal-location query in spatial databases. Given a set S of sites, a set O of weighted objects, and a spatial region Q, the optimal-location query returns a location in Q with maximum influence. Here the influence of a location l is the total weight of its RNNs, i.e. the total weight of objects in O that are closer to l than to any site in S. This new query has practical applications, but is very challenging to solve. Existing work on computing RNNs assumes a single query location, and thus cannot be used to compute optimal locations. The reason is that there are infinite candidate locations in Q. If we check a finite set of candidate locations, the result can be inaccurate, i.e. the revealed location may not have maximum influence. This paper proposes three methods that accurately compute optimal locations. The first method uses a standard R*-tree. To compute an optimal location, the method retrieves certain objects from the R*-tree and sends them as a stream to a plane-sweep algorithm, which uses a new data structure called the aSB-tree to ensure query efficiency. The second method is based on a new index structure called the OL-tree, which novelly extends the k-d-B-tree to store segmented rectangular records. The OL-tree is only of theoretical usage for it is not space efficient. The most practical approach is based on a new index structure called the Virtual OL-tree. These methods are theoretically and experimentally evaluated.
3398773
On Computing Top-t Most Influential Spatial Sites
Given a set O of weighted objects, a set S of sites, and a query site s, the bichromatic RNN query computes the influence set of s, or the set of objects in O that consider s as the nearest site among all sites in S. The influence of a site s can be defined as the total weight of its RNNs. This paper addresses the new and interesting problem of finding the top-t most influential sites from S, inside a given spatial region Q. A straightforward approach is to find the sites in Q, and compute the RNNs of every such site. This approach is not efficient for two reasons. First, all sites in Q need to be identified whatsoever, and the number may be large. Second, both the site R-tree and the object R-tree need to be browsed a large number of times. For each site in Q, the R-tree of sites is browsed to identify the influence region -- a polygonal region that may contain RNNs, and then the R-tree of objects is browsed to find the RNN set. This paper proposes an algorithm called TopInfluential-Sites, which finds the top-t most influential sites by browsing both trees once systematically. Novel pruning techniques are provided, based on a new metric called minExistDNN. There is no need to compute the influence for all sites in Q, or even to visit all sites in Q. Experimental results verify that our proposed method outperforms the straightforward approach.
9271812
Storing and querying multiversion XML documents using durable node numbers
Managing multiple versions of XML documents represents an important problem for many traditional applications, such as software configuration control, as well as new ones, such as link permanence of web documents. Research on managing multiversion XML documents seeks to provide efficient and robust techniques for storing, retrieving and querying such documents. In this paper we present a novel approach to version management that achieves these objectives by a scheme based on Durable Node Numbers and timestamps for the elements of XML documents. We first present efficient storage and retrieval techniques for multiversion documents. Then, we explore the indexing and clustering strategies needed to assure efficient support for complex queries on content and on document evolution.
5927964
Improving min/max aggregation over spatial objects
We examine the problem of computing MIN/MAX aggregates over a collection of spatial objects. Each spatial object is associated with a weight (value), for example, the average temperature or rainfall over the area covered by the object. Given a query rectangle, the MIN/MAX problem computes the minimum/maximum weight among all objects intersecting the query rectangle. Traditionally such queries have been performed as range search queries. Assuming that the objects are indexed by a spatial access method, the MIN/MAX is computed as objects are retrieved. This requires effort proportional to the number of objects intersecting the query interval, which may be large. A better approach is to maintain aggregate information among the index nodes of the spatial access method; then various index paths can be eliminated during the range search. In this paper we propose four optimizations that further improve the performance of MIN/MAX queries. Our experiments show that the proposed optimizations offer drastic performance improvement over previous approaches. Moreover, as a by-product of this work we present an optimized version of the MSB-tree, an index that has been proposed for the MIN/MAX computation over 1-dimensional interval objects.
86297
Continuous Evaluation of Monochromatic and Bichromatic Reverse Nearest Neighbors
This paper presents a novel algorithm for Incremental and General Evaluation of continuous Reverse Nearest neighbor queries (IGERN, for short). The IGERN algorithm is general as it is applicable for both the monochromatic and bichromatic reverse nearest neighbor queries. The incremental aspect of IGERN is achieved through determining only a small set of objects to be monitored. While previous algorithms for monochromatic queries rely mainly on monitoring six pie regions, IGERN takes a radical approach by monitoring only a single region around the query object. The IGERN algorithm clearly outperforms the state-of-the-art algorithms in monochromatic queries. In addition, the IGERN algorithm presents the first attempt for continuous evaluation of bichromatic reverse nearest neighbor queries. The computational complexity of IGERN is presented in comparison to the state-of-the-art algorithms in the monochromatic case and to the use of Voronoi diagrams for the bichromatic case. In addition, the correctness of IGERN in both the monochromatic and bichromatic cases are proved. Extensive experimental analysis shows that IGERN is efficient, is scalable, and outperforms previous techniques for continuous reverse nearest neighbor queries.
1978214
A Language Modeling Approach to Passage Question Answering
This paper reports our efforts on developing a language modeling approach to passage question answering. In particular, we address the following two problems: (i) generalized language modeling for question classification; (ii) constrained language modeling for passage retrieval.
11522705
A supply chain network equilibrium model with random demands
Abstract In this paper, we develop a supply chain network model consisting of manufacturers and retailers in which the demands associated with the retail outlets are random. We model the optimizing behavior of the various decision-makers, derive the equilibrium conditions, and establish the finite-dimensional variational inequality formulation. We provide qualitative properties of the equilibrium pattern in terms of existence and uniqueness results and also establish conditions under which the proposed computational procedure is guaranteed to converge. Finally, we illustrate the model through several numerical examples for which the equilibrium prices and product shipments are computed. This is the first supply chain network equilibrium model with random demands for which modeling, qualitative analysis, and computational results have been obtained.
42579325
A data model and algebra for the Web
The recent emergence of XML as a standard for representation and exchange of data on the Web has drawn significant attention. But existing semistructured data models, such as OEM, cannot support XML naturally and fully. A new data model named XOM is proposed in this paper as the common data model for the Web data source. Based on rooted connected directed graphs both cyclic and acyclic, whose nodes are labeled and edges are ranked, XOM can describe the aggregation relationship as well as the general reference relationship (linkage) between XML elements. Through ranked closure operation, both tree-oriented and graph-oriented models can be unified in XOM. As the formal foundation for query processing and optimization for Web data, a new algebra called XOM algebra, which includes six operations, i.e., object union, difference, select, project, paste and cut, is also proposed. In comparison with relational algebra, XOM algebra is more flexible and powerful.
8370711
Consistency of Action Descriptions
As a contribution to the metatheory of reasoning about actions, we present some characteristics of the consistency of action theories. Three levels of consistency are investigated for the evaluation of action descriptions: uniform consistency, consistency of formulas and regional consistency. The first two provide an intuitive resolution of problems of explanation conflicts and fluent dependency. The concept of regional consistency provides for a measure of ramification. A highly expressive form of action descriptions, the normal form, is introduced to facilitate this analysis. The relative satisfiability of the situation calculus is generalized to accommodate non-deterministic effects and ramifications.
18688530
Web taxonomy integration through co-bootstrapping
We address the problem of integrating objects from a source taxonomy into a master taxonomy. This problem is not only currently pervasive on the web, but also important to the emerging semantic web. A straightforward approach to automating this process would be to learn a classifier that can classify objects from the source taxonomy into categories of the master taxonomy. The key insight is that the availability of the source taxonomy data could be helpful to build better classifiers for the master taxonomy if their categorizations have some semantic overlap. In this paper, we propose a new approach, co-bootstrapping, to enhance the classification by exploiting such implicit knowledge. Our experiments with real-world web data show substantial improvements in the performance of taxonomy integration.