A graph based sliding window multi join over data stream

Join operation is a critical problem when dealing with sliding window over data streams. There have been many optimization strategies for sliding window join in the literature, but a simple heuristic is always used for selecting the join sequence of many sliding windows, which is ineffectively. The graphbased approach is proposed to process the problem. The sliding window join model is introduced primarily. In this model vertex represent join operator and edge indicated the join relationship among sliding windows. Vertex weight and edge weight represent the cost of join and the reciprocity of join operators respectively. Then good query plan with minimal cost can be found in the model. Thus a complete join algorithm combining setting up model, finding optimal query plan and executing query plan is shown. Experiments show that the graphbased approach is feasible and can work better in above environment     

Multidimensional Data Querying on Tree-Structured Overlay

Multidimensional data query has been gaining much interest in database research communities in recent years, yet many of the existing studies focus mainly on ten tralized systems. A solution to querying in Peer-to-Peer（P2P） environment was proposed to achieve both low processing cost in terms of the number of peers accessed and search messages and balanced query loads among peers. The system is based on a balanced tree structured P2P network. By partitioning the query space intelligently, the amount of query forwarding is effectively controlled, and the number of peers involved and search messages are also limited. Dynamic load balancing can be achieved during space partitioning and query resolving. Extensive experiments confirm the effectiveness and scalability of our algorithms on P2P networks.     

A solution to the anonymity of the mobile subscriber

The user anonymity mechanism provided in GSM and UMTS network is analyzed,and a new approach to solve the anonymity of mobile subscriber is proposed in this paper.Using the ciphering algorithm with a dynamic key and a static key,the method allows mobile subscribers to connect network with user anonymity,and it can be seamlessly integrated with the existing authentication algorithms.The analyses reveal that the proposed scheme can provide the integrity protection of messages,prevent the replay attacks,and be implemented easily.     

An Efficient Algorithm for Query Transformation in Semantic Query Optimization

Semantic query optimization (SQO)is comparatively a recent approach for the transformation of given query into equivalent alternative query using matching rules in order to select an optimal query based on the costs of executing alternative queries,The key aspect of the algorthm proposed here is that previous proposed SQO techniques can be considered equally in the uniform cost model,with which optimization opportunities will not be missed.At the same time,the authors used the implication closure to guarantee that any matched rule will not be lost .The authors implemented their algorithm for the optimization of decomposed sub-query in local database in MultiDatabase Integrator(MDBI),which is a multidatabase project.The experimental results verify that this algorithm is effective in the process of SQO.     

Indexing large moving objects from past to future with PCFI

In moving object database,the moving objects’current position must be kept in memory,also to the trajectory,in some case,as same as the future. But the current existing indexes such as SEB-tree,SETI-tree,2+3R-tree,2-3RT-tree and etc. can only provide the capability for past and current query,and the TPR-Tree,TPR* -Tree and et. can only provide the capability for current and future query. None of them can provide a strategy for indexing the past,current and also the future information of moving objects. In this paper,we propose the past-current-future Index (PCFI-Index) to index the past,current & future information of the moving objects. It is the combination of SETI-tree and TPR*-tree,the SETI liking index is used for indexing the historical trajectory segments except the front line structure,and the moving objects’ current positions,velocities are indexed via the in-memory frontline strucltre which mainly implemented with TPR*-tree. Considering the large update operations on TPR-tree of large population,a hash table considering cache sensitivity is also introduced. It works with the frontline part,leading a bottom-up update of the tree. The performance analysis proves that the PCFI-iidex can handle most of the query efficiently and provides a uniform solution for the trajectory query,time-slice query,internal query and moving query.     

Structured plan and its execution for extended goals

In many real world planning domains, some observation information is optional and useless to the execution of a plan, and the information acquisition may require some kind of cost. So it is significant to propose a framework for planning with extended goals under partial observability, which can adapt to the idea of observation reduction. In this paper, a method was proposed to solve the problem. The definition of structured plans was given, which can encode sequential, conditional and iterative behaviors, and are expressive enough for dealing with incomplete observation information and with extended goals. In order to express extended goals over subplans and observation information, the interpretation of basic propositions in KCTL and EAGLE (two important languages for expressing temporal requirements in nondeterministic domains) was extended.     

Using the Dempster-Shafer Theory of Evidence to Rank Documents

Multi-source information can be utilized collaboratively to improve the performance of information retrieval. To make full use of the document and collection information, this paper introduces a new information retrieval model that relies on the Dempster-Shafer theory of evidence. Each query-document pair is taken as a piece of evidence for the relevance between a document and a query. The evidence is combined using Dempster’s rule of combination, and the belief committed to the relevance is obtained. Retrieved documents are then ranked according to the belief committed to the relevance. Several basic probability assignments are also proposed. Extensive experiments over the Text REtrieval Conference (TREC) test collection ClueWeb09 show that the proposed model provides performance similar to that of the Vector Space Model (VSM). Under certain probability assignments, the proposed model outperforms the VSM by 63% in terms of mean average precision.     

A Novel Quantitative Analysis Model for Information System Survivability Based on Conflict Analysis

This paper describes a novel quantitative analysis model for system survivability based on conflict analysis, which provides a direct-viewing survivable situation. Based on the three-dimensional state space of conflict, each player's efficiency matrix on its credible motion set can be obtained. The player whose desire is the strongest in all initiates the moving and the overall state transition matrix of information system may be achieved. In addition, the process of modeling and stability analysis of conflict can be converted into a Markov analysis process, thus the obtained results with occurring probability of each feasible situation will help the players to quantitatively judge the probability of their pursuing situations in conflict. Compared with the existing methods which are limited to post-explanation of system's survivable situation, the proposed model is relatively suitable for quantitatively analyzing and forecasting the future development situation of system survivability. The experimental results show that the model may be effectively applied to quantitative analysis for survivability. Moreover, there will be a good application prospect in practice.     

Mata—information generation in distributed information system

The authors discuss the concept of meta-information which is the desription of information system or its subsystems,and proposes algorithms for meta-information generation.Meta-information can be generated in parallel mode and network computation can be used to accelerate meta-information generation.Most existing rough set methods assume information system to be centralized and cannot be applied directly in distributed information system.Data integration ,which is costly,is necessary for such existing methods.However,meta-information integration will eliminate the need of data integration in many cases,since many rough set operations can be done straightforward based on meta-information,and many existing methods can be modified based on meta-information.     

Efficient View-Based 3-D Object Retrieval via Hypergraph Learning

View-based 3-D object retrieval has become an emerging topic in recent years,especially with the fast development of visual content acquisition devices,such as mobile phones with cameras.Extensive research efforts have been dedicated to this task,while it is still difficult to measure the relevance between two objects with multiple views.In recent years,learning-based methods have been investigated in view-based 3-D object retrieval,such as graph-based learning.It is noted that the graph-based methods suffer from the high computational cost from the graph construction and the corresponding learning process.In this paper,we introduce a general framework to accelerate the learning-based view-based 3-D object matching in large scale data.Given a query object Q and one object O from a 3-D dataset D,the first step is to extract a small set of candidate relevant 3-D objects for object O.Then multiple hypergraphs can be constructed based on this small set of 3-D objects and the learning on the fused hypergraph is conducted to generate the relevance between Q and O,which can be further used in the retrieval procedure.Experiments demonstrate the effectiveness of the proposed framework.     

Twig Pattern Matching Based on Compressed Path Labeling Scheme

Holistic twig query processing techniques based on region encoding have been developed to minimize the intermediate results, namely, those root-to-leaf path matches that are not in the final twig results. These algorithms have to scan all the streams of tags in query patterns. However, useless path matches cannot be completely avoided. TJFast which is based on the labeling scheme of Extended Dewey has been proposed to avoid useless intermediate results, and it only needs to access the labels of the leaf query nodes. However, it don＇t concern about the characteristics of elements with the same parent, and it has to merge join all the intermediate results which are evaluated during the first phrase. We propose a new labeling scheme to compress the XML elements which have the same characteristic. Based on the compressed path-labeled streams, a new novel holistic twig query algorithm named CPJoin is designed. Finally, implementation results are provided to show that CPJoin has good performance on both real and synthetic data.     

BloomRouter： A Framework for Dissemination of Compressed XML Stream

As our best knowledge, in the Publish/Subscribe application environment, few research work has been done on the dissemination and routing of compressed XML （extended markup language） data. A high-speed compressed XML data routing and dissemination framework BloomRouter is proposed. In BloomRouter, a Bloom Filter based prefilte ring mechanism is used to filter out compressed XML elements that users do not care; after that an interval tree dis seminator forwards target elements to the corresponding end users by matching the incomming compressed XML elements with indexed users＇ query regions. Based on this framework, we can efficiently filter/query the compressed incoming XML data, and then route the query result to the corresponding subseriber.     

八邻域网格聚类的多样性XML文档近似查询算法

提出了一种基于八邻域网格聚类的多样性XML近似查询算法.首先给出了支持XML文档间语义距离计算的3种编辑操作代价模型,再利用XML文档间的语义距离建立XML文档的向量模型并设计基于八邻域网格的XML文档聚类算法,进而利用聚类过程中得到的物理和逻辑聚类中心对静态有序选择算法的查询评估策略进行优化,这样做只需定位聚类中心所在组群的局部范围,并在该范围内进行目标查询,而无需遍历整个XML数据库,从而快速返回满足用户需求的查询结果.经汽车外形智能化设计实验表明,所提算法的查询速度比静态有序选择算法平均提高了3~4倍.     

基于路径频率树的XML流数据剪切分片技术

与传统数据库对XML数据的处理不同,对XML流数据的处理不仅受实时性的约束,还受存储空间的限制.在Hole-Filler模型的基础上,首先利用XML的查询统计信息,定义了路径频率树,提出了基于兄弟关系的XML流数据剪切分片策略及其算法.在此基础上,提出了基于父子关系的XML流数据剪切分片策略及算法.这两个基于路径频率树的剪切算法有效地提高了XML片段的利用率,增强了XML片段的内聚性.实验结果表明,基于路径频率树的XML剪切算法在剪切时间、查询时间、空间消耗等方面都表现出较好的性能.     

Automatic user goals identification based on anchor text and click-through data

Understanding the underlying goal behind a user＇s Web query has been proved to be helpful to improve the quality of search. This paper focuses on the problem of automatic identification of query types according to the goals. Four novel entropy-based features extracted from anchor data and click-through data are proposed, and a support vector machines （SVM） classifier is used to identify the user＇s goal based on these features. Experi- mental results show that the proposed entropy-based features are more effective than those reported in previous work. By combin- ing multiple features the goals for more than 97% of the queries studied can be correctly identified. Besides these, this paper reaches the following important conclusions： First, anchor-based features are more effective than click-through-based features; Second, the number of sites is more reliable than the number of links; Third, click-distribution- based features are more effective than session-based ones.     

模糊XML关键字查询方法

在实际应用中数据经常存在不确定性和模糊性,因而对模糊XML数据的关键字查询处理成为一种非专业用户的需求.针对模糊XML数据的关键字查询方法进行研究,对模糊XML的关键字查询语义进行分析,提出一种新的模糊XML文档的编码方法 CDewey,该编码方法能够有效地对节点类型进行区分.在此基础上,提出关键字查询算法FIndex Loop,该算法能够准确求解输入关键字的SLCA结果及结果的可能性值,最后通过实验表明此查询方法的有效性.     

Web Database Query Interface Annotation Based on User Collaboration

A vision based query interface annotation meth od is used to relate attributes and form elements in form based web query interfaces, this method can reach accuracy of 82%. And a user participation method is used to tune the result; user can answer ＂yes＂ or ＂no＂ for existing annotations, or manually annotate form elements. Mass feedback is added to the annotation algorithm to produce more accurate result. By this approach, query interface annotation can reach a perfect accuracy.     

A Deep Web Query Interfaces Classification Method Based on RBF Neural Network

This paper proposes a new approach for classification for query interfaces of Deep Web, which extracts features from the form＇s text data on the query interfaces, assisted with the synonym library, and uses radial basic function neural network （RBFNN） algorithm to classify the query interfaces. The applied RBFNN is a kind of effective feed-forward artificial neural network, which has a simple networking structure but features with strength of excellent nonlinear approximation, fast convergence and global convergence. A TEL_8 query interfaces＇ data set from UIUC on-line database is used in our experiments, which consists of 477 query interfaces in 8 typical domains. Experimental results proved that the proposed approach can efficiently classify the query interfaces with an accuracy of 95.67%.     

KDS-CM： A Cache Mechanism Based on Top-K Data Source for Deep Web Query

Caching is an important technique to enhance the efficiency of query processing. Unfortunately, traditional caching mechanisms are not efficient for deep Web because of storage space and dynamic maintenance limitations. In this paper, we present on providing a cache mechanism based on Top-K data source （KDS-CM） instead of result records for deep Web query. By integrating techniques from IR and Top-K, a data reorganization strategy is presented to model KDS-CM. Also some measures about cache management and optimization are proposed to improve the performances of cache effectively. Experimental results show the benefits of KDS-CM in execution cost and dynamic maintenance when compared with various alternate strategies.