网格环境下基于本体的信息检索体系研究

为了优化基于本体的信息检索的处理过程、提高应用系统的可靠性,提出了一种网格环境中基于本体的信息检索体系模型.利用Globus和OGSA-DAI工具进行计算资源和数据资源的管理,整合了闲置资源,提高了资源利用率,同时,将数据访问服务化,统一了接口访问类型.利用工作流模型管理业务流程的执行,实现了对数据的分布式部署,对业务服务的并行执行,能够在一定程度上解决因为信息量庞大、流程算法复杂带来的检索低效问题,提高系统的客错能力.     

Modeling change requests due to faults in a large-scale telecommunication system

It is widely known that a small number of modules in any system are likely to contain the majority of faults. Early identification and consequent attention to such modules may mitigate or prevent many defects. The objective of this study is to use product metrics to build a prediction model of the number of change requests (CRs) that are likely to occur in individual modules during testing. The study first empirically validates eight product metrics, while considering the confounding effects of code size (lines of code). Next, a prediction model of CR outcomes is developed with the validated metrics by utilizing a negative binomial regression that allows over-dispersion. In total, 816 modules written in the Chill programming language were analyzed in a large-scale telecommunication system. There is a positive association between the number of CRs and four product metrics (number of unique operators, unique operands, signals, and library calls) after considering the confounding effect of code size. A prediction model that includes only code size and the number of unique operands provides the best empirical fit.     

Applying ontology-based rules to conceptual modeling: a reflection on modeling decision making

Conceptual modeling represents a domain independently of implementation considerations for purposes of understanding the problem at hand and communicating about it. However, different people may construct different models given the same domain. Variations among correct models, while known and familiar in practice, have hardly been investigated in the literature. Their roots are in the decisions made during the modeling process, where modelers face the need to map reality into modeling constructs. This paper reports an empirical study whose aim is to explore model variations and in particular to examine possible directions for reducing them. Specifically, the study uses a multimethod research paradigm to examine the effect of applying ontology-based modeling rules on modeling decisions as reflected in resulting model variations. The findings of the study provide insights into the variations phenomenon, as well as to the application of ontology-based modeling rules.     

Applying temporal dependence to detect changes in streaming data

Detection of changes in streaming data is an important mining task, with a wide range of real-life applications. Numerous algorithms have been proposed to efficiently detect changes in streaming data. However, the limitation of existing algorithms is that they assume that data are generated independently. In particular, temporal dependencies of data in a stream are still not thoroughly studied. Motivated by this, in this work we propose a new efficient method to detect changes in streaming data by exploring the temporal dependencies of data in the stream. As part of this, we introduce a new statistical model called the Candidate Change Point (CCP) model, with which the main idea is to compute the probabilities of finding change points in the stream. The computed probabilities are used to generate a distribution, which is, in turn, used in statistical hypothesis tests to determine the candidate changes. We use the CCP model to develop a new algorithm called Candidate Change Point Detector (CCPD), which detects change points in linear time, and is thus applicable for real-time applications. Our extensive experimental evaluation demonstrates the efficiency and the feasibility of our approach.     

Exploiting geographic references of documents in a geographical information retrieval system using an ontology-based index

Both Geographic Information Systems and Information Retrieval have been very active research fields in the last decades. Lately, a new research field called Geographic Information Retrieval has appeared from the intersection of these two fields. The main goal of this field is to define index structures and techniques to efficiently store and retrieve documents using both the text and the geographic references contained within the text. We present in this paper two contributions to this research field. First, we propose a new index structure that combines an inverted index and a spatial index based on an ontology of geographic space. This structure improves the query capabilities of other proposals. Then, we describe the architecture of a system for geographic information retrieval that defines a workflow for the extraction of the geographic references in documents. The architecture also uses the index structure that we propose to solve pure spatial and textual queries as well as hybrid queries that combine both a textual and a spatial component. Furthermore, query expansion can be performed on geographic references because the index structure is based in an ontology.     

Applying the information bottleneck to statistical relational learning

In this paper we propose to apply the Information Bottleneck (IB) approach to the sub-class of Statistical Relational Learning (SRL) languages that are reducible to Bayesian networks. When the resulting networks involve hidden variables, learning these languages requires the use of techniques for learning from incomplete data such as the Expectation Maximization (EM) algorithm. Recently, the IB approach was shown to be able to avoid some of the local maxima in which EM can get trapped when learning with hidden variables. Here we present the algorithm Relational Information Bottleneck (RIB) that learns the parameters of SRL languages reducible to Bayesian Networks. In particular, we present the specialization of RIB to a language belonging to the family of languages based on the distribution semantics, Logic Programs with Annotated Disjunction (LPADs). This language is prototypical for such a family and its equivalent Bayesian networks contain hidden variables. RIB is evaluated on the IMDB, Cora and artificial datasets and compared with LeProbLog, EM, Alchemy and PRISM. The experimental results show that RIB has good performances especially when some logical atoms are unobserved. Moreover, it is particularly suitable when learning from interpretations that share the same Herbrand base.     

Using information flow analysis to detect implicit information leaks for web service composition

Information leak, which can undermine the compliance of web-service-composition business processes for some policies, is one of the major concerns in web service composition. We present an automated and effective approach for the detection of implicit information leaks in business process execution language (BPEL) based on information flow analysis. We introduce an adequate meta-model for BPEL representation based on a Petri net for transformation and analysis. Building on the concept of Petri net place-based noninterference, the core contribution of this paper is the application of a Petri net reachability graph to estimate Petri net interference and thereby to detect implicit information leaks in web service composition. In addition, a case study illustrates the application of the approach on a concrete workflow in BPEL notation.     

Estimation of a data-collection maturity model to detect manufacturing change

Data mining methods have been successfully used for analyzing production data in manufacturing, and generally the production samples are considered derived from a population from the statistical view. However, the assumption is often challenged, because a production system is normally highly interrelated with a manufacturing environment that is time-dependent. Therefore, instead of treating data as elements from a population following a certain distribution, this research considers that, in the whole course of data collection, a total data set might reasonably be divided into three phases as a more accurate production profile: early phase, mature phase, and oversized phase. In the early phase, the data set is usually small and the information extracted is fragile; in the mature phase, the data collected can provide sufficient and stable knowledge to the management; and in the oversized phase, since the system has substantially changed, many old data are no longer current so that their representability has declined. Based on this concept, the two critical points that segment the total data set into three parts are systematically determined here using neural network technologies; and the manufacturing model can be reformed for advancing its predictive capability.     

Applying Occam's razor to global agricultural land use change

We present a parsimonious agricultural land-use model that is designed to replicate global land-use change while allowing the exploration of uncertainties in input parameters. At the global scale, the modelled uncertainty range of agricultural land-use change covers observed land-use change. Spatial patterns of cropland change at the country level are simulated less satisfactorily, but temporal trends of cropland change in large agricultural nations were replicated by the model. A variance-based global sensitivity analysis showed that uncertainties in the input parameters representing to consumption preferences are important for changes in global agricultural areas. However, uncertainties in technological change had the largest effect on cereal yields and changes in global agricultural area. Uncertainties related to technological change in developing countries were most important for modelling the extent of cropland. The performance of the model suggests that highly generalised representations of socio-economic processes can be used to replicate global land-use change.     

Applying statistical principles to data fusion in information retrieval

Data fusion in information retrieval has been investigated by many researchers and quite a few data fusion methods have been proposed. However, their effect on effectiveness has not been well understood. In this paper, we apply statistical principles to data fusion and obtain some useful conclusions, which can be used as a guideline for data fusion methods. Based on that, CombSum, the linear combination methods, and the correlation methods can be justified in certain conditions. We also investigate how to improve the effectiveness of some existing data fusion methods such as CombSum and the linear combination method. Experimental results with TREC data are reported to support the conclusions.     

Applying system dynamics to courseware development

The general purpose of the work reported here is to extend and validate system dynamics technologies for their use in managing the complexities and risks of large scale, courseware development projects. Courseware refers to a variety of computer-based instructional materials used for the purpose of creating effective learning environments. While the costs for computer hardware are generally declining, new hardware and software technologies are appearing with a frequency that makes it a serious challenge to hire and train designers, developers and project managers and to plan and produce computer-based instructional materials that are both effective (in terms of learning) and efficient (in terms of costs and technology utilization).     

Applying domain knowledge and social information to product analysis and recommendations: an agent-based decision support system

Abstract: The advance of Internet and Web technologies has boosted the development of electronic commerce. More and more people have changed their traditional trading behaviors and started to conduct Internet shopping. However, the exponentially increasing product information provided by Internet enterprises causes the problem of information overload, and this inevitably reduces the customer's satisfaction and loyalty. To overcome this problem, in this paper we propose a multi‐agent system that is capable of eliciting expert knowledge and of recommending optimal products for individual consumers. The recommendations are based on both product knowledge from domain experts and the customer's preferences from system–consumer interactions. In addition, the system also uses behavior patterns collected from previous consumers to predict what the current consumer may expect. Experiments have been conducted and the results show that our system can give sensible recommendations, and it is able to adapt to the most up‐to‐date preferences for the customers.     

Utilizing image texture to detect land-cover change in Mediterranean coastal wetlands

Land-use/cover change dynamics were investigated in a Mediterranean coastal wetland. Change Vector Analysis (CVA) without and with image texture derived from the co-occurrence matrix and variogram were evaluated for detecting land-use/cover change. Three Landsat Thematic Mapper (TM) scenes recorded on July 1985, 1993 and 2005 were used, minimizing change detection error caused by seasonal differences. Images were geometrically, atmospherically and radiometrically corrected. CVA without and with texture measures were implemented and assessed using reference images generated by object-based supervised classification. These outputs were used for cross-classification to determine the ‘from–to’ change used to compare between techniques. The Landsat TM image bands together with the variogram yielded the most accurate change detection results, with Kappa statistics of 0.7619 and 0.7637 for the 1985–1993 and 1993–2005 image pairs, respectively.     

小波的文本图像区分及其在文献信息数字化中的应用

目前,OCR技术对文本图像区域自动区分的效果还不够精确,进而影响了OCR技术在文献信息数字化过程中的工作效率.针对这一局限,提出了一种基于小波的文本图像区分方法.方法首先对扫描区域进行小波分解,然后使用分解系数构建分解能量,最后依据分解能量大小对文本图像进行自动区分.结果表明,该方法对文本图像的区分效果较好,减少了在使用OCR技术进行文献信息数字化时的人为干预,有利于提高文献信息数字化过程的自动化水平.最后通过实验仿真验证了该方法的有效性.     

Applying Virtual Reality to Molecular Graphics System

Mlecular graphics can be thought of as a window to the computer through which the chemist expresses ideas for computational evaluation and receives results in an understandable form.Furthermore,with beautiful graphic images it can give out the realistic molecular model like a real thing in real world.Molecule has various properties including volume,electronic,van der waals forces,etc.These properties are very important to understand the molecular world.So if the virtual reality tools are used,then the imaginary world can be studied intuitively by touching and feeling a tremendous amount of data.Computational chemistry generates such amount of molecular property data through supercomputing with molecular simulation experiment.One of the objects to investigate the molecular world is to understand the intermolecular interaction such as drug-receptor interaction.Another thing is to measure the geometrical data in molecular architecture.Virtual reality system provides the easiest way to meet these objects.This kind of simple system changes a numerical data set,which is very difficults to deal with,into a visible and understandable data set.Recently two functions of such a system were improved to get an insight into biomolecular interaction.The first one is a real time force generation during navigation in macromolecular environment.An cylindrical arrow shows the magnitude and direction of molecular force.The second one is to see a molecular vibration such as a concerted motion of the binding site in protein molecule.So one can understand th molecular shape change for drugreceptor docking procedure.But some problems which are difficult to solve still remain.     

Applying expert system techniques to human genetics

Although expert systems have been developed in a variety of medical areas, there has been very little application of expert system techniques to the field of human genetics. The purpose of the research project described in this paper was (1) to experiment with different types of knowledge representation for data and knowledge structures in human genetics and (2) to explore the applicability of different inference mechanisms for various genetic problems. We present an object-oriented and a fact-based model for the representation of genealogical information and describe two prototype systems.