32169632
GiSA: A Grid System for Genome Sequences Assembly
Sequencing genomes is a fundamental aspect of biological research. Shotgun sequencing, since introduced by Sanger et al [2], has remained the mainstay in the research field of genome sequence assembly. This method randomly obtains sequence reads (e.g. a subsequence including about 500 characters) from a genome and then assemblies them into contigs based on significant overlap among them. The whole-genome shotgun (WGS) approach, generates sequence reads directly from a whole-genome library and uses computational techniques to reassemble them. A variety of assembly programs have been previously proposed and implemented, including PHRAP [3] (Green 1994), CAP3 [4] (1999), Celera [5] (2000) etc. Because of great computational complexity and increasingly large size, they incur great time and space overhead. PHRAP [3], for instance, which can only run in a stand-alone way, requires many times memory (usually greater than 10) as the size of original sequence data. In realistic applications, sequencing process might come to become unacceptably slow for insufficient memory even with a mainframe with huge RAM.
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.
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.
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.
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.
35130672
A framework towards efficient and effective sequence clustering
Analyzing sequence data (particularly in categorical domains) has become increasingly important, partially due to the significant advances in biology and other fields. Examples of sequence data include DNA sequences, unfolded protein sequences, text documents, Web usage data, system traces, etc. Previous work on mining sequence data has mainly focused on frequent pattern discovery. In this project, we focus on the problem of clustering sequence data.
119016
Towards automatic clustering of protein sequences
Analyzing protein sequence data becomes increasingly important recently. Most previous work on this area has mainly focused on building classification models. In this paper we investigate in the problem of automatic clustering of unlabeled protein sequences. As a widely recognized technique in statistics and computer science, clustering has been proven very useful in detecting unknown object categories and revealing hidden correlations among objects. One difficulty, that prevents clustering from being performed directly on protein sequence is the lack of an effective similarity measure that can be computed efficiently. Therefore, we propose a novel model for protein sequence cluster by exploring significant statistical properties possessed by the sequences. The concept of imprecise probabilities are introduced to the original probabilistic suffix tree to monitor the convergence of the empirical measurement and to guide the clustering process. It is demonstrated that the proposed method can successfully discover meaningful families without the necessity of learning models of different families from pre-labeled "training data".
46086053
Similarity Join Algorithms: An Introduction
A multi-function type sheet counting machine capable of counting sheets under a desired operational mode selected from a plurality of operational modes. As the sheets to be counted are deflected one after another away from a stack of sheets, electrical count pulses corresponding to the number of deflected sheets are generated, and a count corresponding to the number of generated pulses is stored in a counter. A reset circuit is provided so that, at the time of changing over to the add mode from any other operational mode, the counter is automatically reset to clear the count previously stored in the counter.
3430950
Efficient Processing of XML Path Queries Using the Disk-based F&B Index
With the proliferation of XML data and applications on the Internet, efficient XML query processing techniques are in great demand. Answering queries using XML indexes is a natural approach. A number of XML indexes have been proposed in the literature: among them, FB the result is a disk-based F&B Index with good clustering properties. In addition, novel query processing algorithms exploiting the physical organization of the disk-based F&B Indexes are proposed. Experimental results verify that our disk-based F&B Index can scale up for large data size with good query performance compared with state-of-the-art XML query processing algorithms.
56789286
Dynamo: design, implementation, and evaluation of cooperative persistent object management in a local area network
In light of advances in processor and networking technology, especially the emergence of network attached disks, the traditional client-server architecture of persistent storage systems has become suboptimal for many computation/data intensive applications. In this paper, we introduce a revised architecture for persistent object management employing network attached storage: the dynamic object server environment (Dynamo). Dynamo introduces two main architectural innovations: (1) to provide high scalability, the object management functions are mainly performed cooperatively by the clients in the system. Furthermore, data is transferred directly to the client's cache from network-attached disks, thus avoiding copies from a disk to the server buffer and then over the network to the client. Other systems have an a priori assignment of ‘object management’ functions to specific nodes; (2) Dynamo uses a cooperative cache management which employs a decentralized lottery-based page replacement strategy with a novel technique which attempts to put a page replaced from one node into the cache of another node which is likely to access the page in the near future. We show via performance benchmarks run on the Dynamo system and simulation results how this architecture increases the system's adaptability, scalability and cost performance. Copyright © 2000 John Wiley & Sons, Ltd.