11863469
Processing Spatial-Keyword (SK) Queries in Geographic Information Retrieval (GIR) Systems
Location-based information contained in publicly available GIS databases is invaluable for many applications such as disaster response, national infrastructure protection, crime analysis, and numerous others. The information entities of such databases have both spatial and textual descriptions. Likewise, queries issued to the databases also contain spatial and textual components, for example, "Find shelters with emergency medical facilities in Orange County," or "Find earthquake-prone zones in Southern California." We refer to such queries as spatial-keyword queries or SK queries for short. In recent times, a lot of interest has been generated in efficient processing of SK queries for a variety of applications from Web-search to GIS decision support systems. We refer to systems built for enabling such applications as Geographic Information Retrieval (GIR) Systems. An example GIR system that we address in this paper is a search engine built on top of hundreds of thousands of publicly available GIS databases. Building a search engine over such large repositories is a challenge. One of the key aspects of such a search engine is the performance. In this paper, we propose a framework for GIR systems and focus on indexing strategies that can process SK queries efficiently. We show through experiments that our indexing strategies lead to significant improvement in efficiency of answering SK queries over existing techniques.
3193010
NNH: Improving Performance of Nearest-Neighbor Searches Using Histograms
Efficient search for nearest neighbors (NN) is a fundamental problem arising in a large variety of applications of vast practical interest. In this paper we propose a novel technique, called NNH (“Nearest Neighbor Histograms”), which uses specific histogram structures to improve the performance of NN search algorithms. A primary feature of our proposal is that such histogram structures can co-exist in conjunction with a plethora of NN search algorithms without the need to substantially modify them. The main idea behind our proposal is to choose a small number of pivot objects in the space, and pre-calculate the distances to their nearest neighbors. We provide a complete specification of such histogram structures and show how to use the information they provide towards more effective searching. In particular, we show how to construct them, how to decide the number of pivots, how to choose pivot objects, how to incrementally maintain them under dynamic updates, and how to utilize them in conjunction with a variety of NN search algorithms to improve the performance of NN searches. Our intensive experiments show that nearest neighbor histograms can be efficiently constructed and maintained, and when used in conjunction with a variety of algorithms for NN search, they can improve the performance dramatically.
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.
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.
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.
8850461
Schema-guided wrapper maintenance for web-data extraction
Extracting data from Web pages using wrappers is a fundamental problem arising in a large variety of applications of vast practical interests. There are two main issues relevant to Web-data extraction, namely wrapper generation and wrapper maintenance. In this paper, we propose a novel schema-guided approach to the problem of automatic wrapper maintenance. It is based on the observation that despite various page changes, many important features of the pages are preserved, such as syntactic patterns, annotations, and hyperlinks of the extracted data items. Our approach uses these preserved features to identify the locations of the desired values in the changed pages, and repair wrappers correspondingly by inducing semantic blocks from the HTML tree. Our intensive experiments on real Web sites show that the proposed approach can effectively maintain wrappers to extract desired data with high accuracies.
218270
Cryptanalysis of a multistage encryption system
This paper analyzes the security of a new multistage encryption system (MES) recently proposed in ISCAS'2004. It is found that MES is insecure against a differential chosen-plaintext/ciphertext attack. Experiments are given to support the proposed attack. It is also pointed out that the security of MES against brute-force attacks is not sufficiently high.
17572048
Supporting ad-hoc ranking aggregates
This paper presents a principled framework for efficient processing of ad-hoc top-k (ranking) aggregate queries, which provide the k groups with the highest aggregates as results. Essential support of such queries is lacking in current systems, which process the queries in a naïve materialize-group-sort scheme that can be prohibitively inefficient. Our framework is based on three fundamental principles. The Upper-Bound Principle dictates the requirements of early pruning, and the Group-Ranking and Tuple-Ranking Principles dictate group-ordering and tuple-ordering requirements. They together guide the query processor toward a provably optimal tuple schedule for aggregate query processing. We propose a new execution framework to apply the principles and requirements. We address the challenges in realizing the framework and implementing new query operators, enabling efficient group-aware and rank-aware query plans. The experimental study validates our framework by demonstrating orders of magnitude performance improvement in the new query plans, compared with the traditional plans.
10820274
Simultaneous and exact interval estimates for the contrast of two groups based on an extremely high dimensional variable: application to mass spec data
MOTIVATION
Analysis of high-throughput proteomic/genomic data, in particular, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) data and microarray data, has led to a multitude of techniques aimed at identifying potential biomarkers. Most of the statistical techniques for comparing two groups are based on qualitative measures such as P-value. A quantitative way such as interval estimation for the contrasts of two groups is more appealing.


RESULTS
We have devised a simultaneous confidence bands method capable of detecting potential biomarkers, while controlling for overall confidence coverage level, in high-dimensional datasets that discriminate two treatment groups using a permutation scheme. For example, for the SELDI-TOF MS data, we deal with the entire spectrum simultaneously and construct (1 - alpha) confidence bands for the mean differences between groups. Furthermore, peaks were identified based on the maximal differences between the groups as determined by the confidence bands. The analysis method herein described gives both qualitative (P-value) and quantitative data (magnitude of difference). The Clinical Proteomics Programs Databank's ovarian cancer dataset and data from in-house samples containing known spiked-in proteins were analyzed. We were able to identify potential biomarkers similar to those described in previous analysis of the ovarian cancer data, however, while these markers are highly significant between cancer and normal groups, our analysis indicated the absolute difference between the two groups was minimal. In addition, we found additional markers than those previously described with greater differences in average intensities. The proposed confidence bands method successfully detected the spiked-in peaks, as well as, secondary peaks generated by adducts and double-charged species. We also illustrate our method utilizing paired gene expression data from a prostate cancer microarray experiment by constructing confidence bands for the fold changes between cancer and normal samples.


AVAILABILITY
R-package, 'seie.zip' (license: GNU GPL), is publiclly available at http://research2.dfci.harvard.edu/dfci/MS_spike-in_data/
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.
34090759
Segmentation of external force field for automatic initialization and splitting of snakes
Active contours or snakes have been extensively utilized in handling image segmentation and classification problems. In traditional active contour models, snake initialization is performed manually by users, and topological changes, such as splitting of the snake, cannot be automatically handled. In this paper, we introduce a new method to solve the snake initialization and splitting problem, based on an area segmentation approach: the external force field is segmented first, and then the snake initialization and splitting can be automatically performed by using the segmented external force field. Such initialization and splitting produces multiple snakes, each of which is within the capture range associated to an object and will be evolved to the object boundary. The external force used in this paper is a gradient vector flow with an edge-preserving property (EPGVF), which can prevent the snakes from passing over weak boundaries. To segment the external force field, we represent it with a graph, and a graph-theory approach can be taken to determine the membership of each pixel. Experimental results establish the effectiveness of the proposed approach.