26642486
Computing Repairs for Inconsistent XML Document Using Chase
An XML document is inconsistent if it violates predefined integrity constraints. In this paper, we consider how to compute repairs for an inconsistent XML document. Here repair is defined as the data consistent with the integrity constraints, and also minimally differs from the original document. Based on a repair framework by introducing a chase method, in this paper, we discuss the repairs computing problem and implement a prototype. First we discuss some key points about mends generation and repairs chasing. Next we give a cost model for this repair framework, which can be used to evaluate the cost of each repair. Finally we implement prototypes of our method, and evaluate our framework and algorithms in the experiment.
10409272
Repairing Inconsistent XML Documents
XML document may contain inconsistencies that violate predefined integrity constraints, and there are two basic concepts for this problem: Repair is the data consistent with the integrity constraints, and also minimally differs from the original one. Consistent data is the data common for every possible repair. In this paper, first we give a general constraint model for XML, which can express functional dependencies, keys and multivalued dependencies. Next we provide a repair framework for inconsistent XML document with three basic update operations: node insertion, node deletion and value modification. Following this approach, we introduce the concept of repair for inconsistent XML document, discuss the chase process to generate repairs, and prove some important properties of the chase process. Finally we give a method to obtain the greatest lower bound of all possible repairs, which is sufficient for consistent data.
30881426
Constraint-Based Graph Mining in Large Database
Currently, constraints are increasingly considered as a kind of means of user- or expert-control for filtering those unsatisfied and redundant patterns rapidly during the web mining process. Recent work has highlighted the importance of constraint-based mining paradigm in the context of frequent itemsets, sequences, and many other interesting patterns in large database. However, it is still not clear how to push various constraints systematically into graph mining process. In this paper, we categorize various graph-based constraints into several major classes and develop a framework CabGin (i.e. C onstr a int- b ased G raph M in ing) to push them into mining process by their categories. Non-monotonic aggregates like average also can be pushed into CabGin with minor revision. Experimental results show that CabGin can prunes a large search space effectively by pushing graph-based constraints into mining process.
14792668
Personalization as a service: the architecture and a case study
Cloud computing has become a hot topic in the IT industry. Great efforts have been made to establish cloud computing platforms for enterprise users, mostly small businesses. However, there are few researches about the impact of cloud computing over individual users. In this paper we focus on how to provide personalized services for individual users in the cloud environment. We argue that a personalized cloud service shall compose of two parts. The client side program records user activities on personal de-vices such as PC. Besides that, the user model is also computed on the client side to avoid server overhead. The cloud side program fetches the user model periodically and adjusts its results accordingly. We build a personalized cloud data search engine prototype to prove our idea.
8249361
SUDEPHIC: Self-Tuning Density-Based Partitioning and Hierarchical Clustering
Clustering is one of the primary techniques in data mining, for which to find the user expecting result is a major issue. However, to dynamically specify the parameters for clustering algorithms presents an obstacle for users. This paper firstly introduces a novel density-based partitioning and hierarchical algorithm, which makes it easy to employ synthetic feedback mechanism in clustering. Additionally, by investigating into the relation between parameters and the clustering result, we propose a self-tuning technique for the setting of parameters. Meanwhile, the density distribution within a cluster can be expressed in the result for the user to specify the cluster’s feature. The algorithm is both evaluated in theory and practice. It outperforms many existing algorithms both in efficiency and quality.
207162632
Utility-based anonymization for privacy preservation with less information loss
Privacy becomes a more and more serious concern in applications involving microdata. Recently, efficient anonymization has attracted much research work. Most of the previous methods use global recoding, which maps the domains of the quasi-identifier attributes to generalized or changed values. However, global recoding may not always achieve effective anonymization in terms of discernability and query answering accuracy using the anonymized data. Moreover, anonymized data is often used for analysis. As well accepted in many analytical applications, different attributes in a data set may have different utility in the analysis. The utility of attributes has not been considered in the previous methods.
 In this paper, we study the problem of utility-based anonymization. First, we propose a simple framework to specify utility of attributes. The framework covers both numeric and categorical data. Second, we develop two simple yet efficient heuristic local recoding methods for utility-based anonymization. Our extensive performance study using both real data sets and synthetic data sets shows that our methods outperform the state-of-the-art multidimensional global recoding methods in both discernability and query answering accuracy. Furthermore, our utility-based method can boost the quality of analysis using the anonymized data.
17247210
Identities on Bell polynomials and Sheffer sequences
In this paper, we study exponential partial Bell polynomials and Sheffer sequences. Two new characterizations of Sheffer sequences are presented, which indicate the relations between Sheffer sequences and Riordan arrays. Several general identities involving Bell polynomials and Sheffer sequences are established, which reduce to some elegant identities for associated sequences and cross sequences.
6483143
Using Proximity in Query Focused Multi-document Extractive Summarization
The query focused multi-document summarization tasks usually tend to answer the queries in the summary. In this paper, we suggest introducing an effective feature which can represent the relation of key terms in the query. Here, we adopt the feature of term proximity commonly used in the field of information retrieval, which has improved the retrieval performance according to the relative position of terms. To resolve the problem of data sparseness and to represent the proximity in the semantic level, concept expansion is conducted based on WordNet. By leveraging the term importance, the proximity feature is further improved and weighted according to the inverse term frequency of terms. The experimental results show that our proposed feature can contribute to improving the summarization performance.
20360088
Commentary on an open question
Abstract In this commentary, we give the triangular recurrence relations for the elements of the matrix T  = ( T i , j ) =  L 1 D −1 S 1 and its inverse T - 1 = ( T ¯ i , j ) = S 2 DL 1 - 1 , respectively, which have also answered the open question put forward by El-Mikkawy. Moreover, with the recurrences, a computational MAPLE program is written to generate the elements of T and T −1 .
26957943
Matching Stream Authentication and Resource Allocation to Multimedia Codec Dependency with Position-Value Partitioning in Wireless Multimedia Sensor Networks
A cross layer Unequal Error Protection (UEP) scheme based upon the multimedia position-value (P-V) partitioning has been recently proposed to only improve energy-distortion performance in Wireless Multimedia Sensor Networks (WMSN). There is also a great potential to adapt this UEP scheme into multimedia stream integrity protection. However, performance gains in multimedia transmissions with considerations of energy, distortion, and authentication in WMSN is a challenge. This difficulty results from the media codec dependency on both the content of multimedia stream authentication and protection on the integrity process itself. In this article, we propose a novel scheme which optimally matches the application layer multimedia codec dependency to both lower layer resource allocation requirements and the upper layer stream authentication. The goal of this scheme is to optimize the integrity and quality performance gain within energy constraint. The contribution of the proposed approach is two folds. Firstly, a stream authentication scheme matched with P-V codec dependency is proposed which significantly reduces additional authentication dependency overhead. Secondly, a new resource allocation scheme is proposed to improve energy-distortion-authentication performance with regard to codec dependency. Simulation studies demonstrate that the proposed scheme significantly impacts achieving multimedia transmission quality with energy efficiency and authentication assurance.
9278394
Keyword search on structured and semi-structured data
Empowering users to access databases using simple keywords can relieve the users from the steep learning curve of mastering a structured query language and understanding complex and possibly fast evolving data schemas. In this tutorial, we give an overview of the state-of-the-art techniques for supporting keyword search on structured and semi-structured data, including query result definition, ranking functions, result generation and top-k query processing, snippet generation, result clustering, query cleaning, performance optimization, and search quality evaluation. Various data models will be discussed, including relational data, XML data, graph-structured data, data streams, and workflows. We also discuss applications that are built upon keyword search, such as keyword based database selection, query generation, and analytical processing. Finally we identify the challenges and opportunities of future research to advance the field.