516020
Efficient Processing of Ordered XML Twig Pattern
Finding all the occurrences of a twig pattern in an XML database is a core operation for efficient evaluation of XML queries. Holistic twig join algorithm has showed its superiority over binary decompose based approach due to efficient reducing intermediate results. The existing holistic join algorithms, however, cannot deal with ordered twig queries. A straightforward approach that first matches the unordered twig queries and then prunes away the undesired answers is obviously not optimal in most cases. In this paper, we study a novel holistic-processing algorithm, called OrderedTJ, for ordered twig queries. We show that OrderedTJ can identify a large query class to guarantee the I/O optimality. Finally, our experiments show the effectiveness, scalability and efficiency of our proposed algorithm.
29028846
Reuse or Never Reuse the Deleted Labels in XML Query Processing Based on Labeling Schemes
To facilitate the XML query processing, several kinds of labeling schemes have been proposed. Based on the labeling schemes, the ancestor-descendant and parent-child relationships in XML queries can be quickly determined without accessing the original XML file. Recently, more researches are focused on how to update the labels when nodes are inserted into the XML. However how to process the deleted labels are not discussed previously. We think that the deleted labels can be processed in two different directions: (1) reuse all the deleted labels to control the label size increasing speed and improve the query performance; (2) never reuse the deleted labels to query different versions of the XML data based on labeling schemes. In this paper, we firstly introduce our previous work, called QED, which can completely avoid the re-labeling in XML updates. Secondly based on QED we propose a new algorithm, called Reuse, which can reuse all the deleted labels to control the label size increasing speed; meanwhile the Reuse algorithm can completely avoid the re-labeling also. Thirdly to query different versions of the XML data, we propose another new algorithm, called NeverReuse, which is the only approach that never reuses any deleted labels. Extensive experimental results show that the algorithms proposed in this paper can control the label size increasing speed when reusing all the deleted labels, and is the only approach to query different versions of the XML data based on labeling schemes.
139092767
An Improved Prefix Labeling Scheme: A Binary String Approach for Dynamic Ordered XML
A number of labeling schemes have been designed to facilitate the query of XML, based on which the ancestor-descendant relationship between any two nodes can be determined quickly. Another important feature of XML is that the elements in XML are intrinsically ordered. However the label update cost is high based on the present labeling schemes. They have to re-label the existing nodes or re-calculate some values when inserting an order-sensitive element. Thus it is important to design a scheme that supports order-sensitive queries, yet it has low label update cost. In this paper, we design a binary string prefix scheme which supports order-sensitive update without any re-labeling or re-calculation. Theoretical analysis and experimental results also show that this scheme is compact compared to the existing dynamic labeling schemes, and it provides efficient support to both ordered and un-ordered queries.
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.
16587000
OWL-Based Semantic Conflicts Detection and Resolution for Data Interoperability
Ontology provides sharing knowledge among different data sources which will help to clarify the semantics of information. OWL is being promoted as a standard for web ontology language, thus in the future a considerable number of ontologies will be created based on OWL. Therefore automatically detecting semantic conflicts based on OWL will greatly expedite the step to achieve semantic interoperability, and will greatly reduce the manual work to detect semantic conflicts. In this paper, we summarize seven cases based on OWL in which semantic conflicts are easily to be encountered, and for each case, we give a rule to resolve the conflict. Via a series of examples, we show how this method works. Based on the seven cases, we propose a semantic conflicts detection and resolution algorithm. This aims at providing a semi-automatic method for semantic uniform data interoperability and integration.
3194322
Efficient record linkage in large data sets
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 constituting the record. The record-linkage problem arises naturally in the context of data cleansing that usually precedes data analysis and mining. We explore a novel approach to this problem. 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 as an example. Given the merging rule that defines when two records are Similar a set of attributes are chosen along which the merge will proceed A multidimensional similarity join over the chosen attributes is used to determine similar pairs of records. Our extensive experiments using real data sets show that our solution has very good efficiency and accuracy.
29013572
Semi-supervised Learning in Medical Image Database
This paper presents a novel graph-based algorithm for solving the semi-supervised learning problem. The graph-based algorithm makes use of the recent advances in stochastic graph sampling technqiue and a modeling of the labeling consistency in semi-supervised learning. The quality of the algorithm is empirically evaluated on a synthetic clustering problem. The semi-supervised clustering is also applied to the problem of symptoms classification in medical image database and shows promising results.
19589601
Single machine scheduling to minimize total compression plus weighted flow cost is NP-hard
Abstract This article analyzes the computational complexity of a single machine scheduling problem to minimize total compression plus weighted flow cost. Vickson [Oper. Res. 28 (1980) 1155–1167] studied this problem and conjectured that it was NP-hard. The complexity of this problem remained open since then. We give a positive answer to this conjecture, showing that this problem is NP-hard.
39036081
Tongue image matching using color content
This paper addresses the problem of color image matching in medical diagnosis. The color matching of tongue images in different color spaces with different metrics have been investigated and is reported in this article. Two new metrics namely, sorted metric and probabilistic combined metric, are proposed. Existing distance measurements in coordinate space do not satisfy the reflexivity axiom. That means, they are not the valid metrics. To overcome this limitation, the sorted metric in coordinate space is proposed in coordinate space. To improve the matching performance, a probabilistic combined metric is proposed based on the theory of combining classifier. These metrics are applied for the matching of tongue color images and the results are encouraging.
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.