17070310
Answering aggregation queries on hierarchical web sites using adaptive sampling
We study how to answer aggregation queries over hierarchical Web sites using adaptive sampling.
2113121
Computing capabilities of mediators
Existing data-integration systems based on the mediation architecture employ a variety of mechanisms to describe the query-processing capabilities of sources. However, these systems do not compute the capabilities of the mediators based on the capabilities of the sources they integrate. In this paper, we proposed a framework to capture a rich variety of query-processing capabilities of data sources and mediators. We present algorithms to compute the set of supported queries of a mediator, based on the capability limitations of its sources. Our algorithms take into consideration a variety of query-processing techniques employed by mediators to enhance the set of supported queries.
10902397
Protecting Individual Information Against Inference Attacks in Data Publishing
In many data-publishing applications, the data owner needs to protect sensitive information pertaining to individuals. Meanwhile, certain information is required to be published. The sensitive information could be considered as leaked, if an adversary can infer the real value of a sensitive entry with a high confidence. In this paper we study how to protect sensitive data when an adversary can do inference attacks using association rules derived from the data. We formulate the inference attack model, and develop complexity results on computing a safe partial table. We classify the general problem into subcases based on the requirements of publishing information, and propose the corresponding algorithms for finding a safe partial table to publish. We have conducted an empirical study to evaluate these algorithms on real data.
7967297
2D BubbleUp: Managing Parallel Disks for Media Servers
In this study we present a scheme called two-dimensional BubbleUp (2DB) for managing parallel disks in a multimedia server. Its goal is to reduce initial latency for interactive multimedia applications, while balancing disk loads to maintain high throughput. The 2DB scheme consists of a data placement and a request scheduling policy. The data placement policy replicates frequently accessed data and places them cyclically throughout the disks. The request scheduling policy attempts to maintain free ``service slots'''' in the immediate future. These slots can then be used to quickly service newly arrived requests. Through examples and simulation, we show that our scheme significantly reduces initial latency and maintains throughput comparable to that of the traditional schemes.
1386080
Using Constraints to Describe Source Contents in Data Integration Systems
In data integration systems, information sources often have constraints, such as "all houses stored at a source have a unique address." These constraints are useful in computing answers to queries and facilitating information exchange.
8510271
Supporting Efficient Record Linkage for Large Data Sets Using Mapping Techniques
This paper describes an efficient approach to record linkage. Given two lists of records, the record-linkage problem consists of determining all pairs that are similar to each other, where the overall similarity between two records is defined based on domain-specific similarities over individual attributes. The record-linkage problem arises naturally in the context of data cleansing that usually precedes data analysis and mining. Since the scalability issue of record linkage was addressed in [21], the repertoire of database techniques dealing with multidimensional data sets has significantly increased. Specifically, many effective and efficient approaches for distance-preserving transforms and similarity joins have been developed. Based on these advances, we explore a novel approach to record linkage. For each attribute of records, we first map values to a multidimensional Euclidean space that preserves domain-specific similarity. Many mapping algorithms can be applied, and we use the Fastmap approach [16] as an example. Given the merging rule that defines when two records are similar based on their attribute-level similarities, a set of attributes are chosen along which the merge will proceed. A multidimensional similarity join over the chosen attributes is used to find similar pairs of records. Our extensive experiments using real data sets show that our solution has very good efficiency and recall.
5215475
QED: a novel quaternary encoding to completely avoid re-labeling in XML updates
The method of assigning labels to the nodes of the XML tree is called a labeling scheme. Based on the labels only, both ordered and un-ordered queries can be processed without accessing the original XML file. One more important point for the labeling scheme is the label update cost in inserting or deleting a node into or from the XML tree. All the current labeling schemes have high update cost, therefore in this paper we propose a novel quaternary encoding approach for the labeling schemes. Based on this encoding approach, we need not re-label any existing nodes when the update is performed. Extensive experimental results on the XML datasets illustrate that our QED works much better than the existing labeling schemes on the label updates when considering either the number of nodes or the time for re-labeling.
35008704
Image segmentation based on a multiresolution Bayesian framework
A multiresolution Markov random field (MMRF) approach to texture segmentation which makes use of both regional and boundary information is proposed in this work. The algorithm is designed to improve the efficiency and solve two problems: over-segmentation and under-segmentation. At each resolution level, regional information and boundary information between textured regions is extracted to describe each block using the multiresolution Fourier transform (MFT). The image is then modelled as a sequence of Markov random fields (MRFs) of varying resolution and a Gibbs sampling scheme is applied to label the constituent sites at each scale by seeking the configuration with minimal interaction energy. The interaction energy is defined as a function of the regional and boundary information. The constraints of region context, and boundary smoothness and connectivity are also encoded in the interaction energy. Once the algorithm converges at a given scale, the segmentation result is propagated down to the next resolution for further refinement.
8267935
Structural Modeling and Analysis of Signaling Pathways Based on Petri Nets
The purpose of this paper is to discuss how to model and analyze signaling pathways by using Petri net. Firstly, we propose a modeling method based on Petri net by paying attention to the molecular interactions and mechanisms. Then, we introduce a new notion "activation transduction component" in order to describe an enzymic activation process of reactions in signaling pathways and shows its correspondence to a so-called elementary T-invariant in the Petri net models. Further, we design an algorithm to effectively find basic enzymic activation processes by obtaining a series of elementary T-invariants in the Petri net models. Finally, we demonstrate how our method is practically used in modeling and analyzing signaling pathway mediated by thrombopoietin as an example.
5432512
RankSQL: query algebra and optimization for relational top-k queries
This paper introduces RankSQL, a system that provides a systematic and principled framework to support efficient evaluations of ranking (top-k) queries in relational database systems (RDBMS), by extending relational algebra and query optimization. Previously, top-k query processing is studied in the middleware scenario or in RDBMS in a "piecemeal" fashion, i.e., focusing on specific operator or sitting outside the core of query engines. In contrast, we aim to support ranking as a first-class database construct. As a key insight, the new ranking relationship can be viewed as another logical property of data, parallel to the "membership" property of relational data model. While membership is essentially supported in RDBMS, the same support for ranking is clearly lacking. We address the fundamental integration of ranking in RDBMS in a way similar to how membership, i.e., Boolean filtering, is supported. We extend relational algebra by proposing a rank-relational model to capture the ranking property, and introducing new and extended operators to support ranking as a first-class construct. Enabled by the extended algebra, we present a pipelined and incremental execution model of ranking query plans (that cannot be expressed traditionally) based on a fundamental ranking principle. To optimize top-k queries, we propose a dimensional enumeration algorithm to explore the extended plan space by enumerating plans along two dual dimensions: ranking and membership. We also propose a sampling-based method to estimate the cardinality of rank-aware operators, for costing plans. Our experiments show the validity of our framework and the accuracy of the proposed estimation model.
3427735
RankSQL: Supporting Ranking Queries in Relational Database Management Systems
Ranking queries (or top-k queries) are dominant in many emerging applications, e.g., similarity queries in multimedia databases, searching Web databases, middleware, and data mining. The increasing importance of top-k queries warrants an efficient support of ranking in the relational database management system (RDBMS) and has recently gained the attention of the research community. Top-k queries aim at providing only the top k query results, according to a user-specified ranking function, which in many cases is an aggregate of multiple criteria. The following is an example top-k query.