15497127
Reasoning About ORA-SS Data Models Using the Semantic Web
There has been a rapid growth in the use of semistructured data in both web applications and database systems. Consequently, the design of a good semistructured data model is essential. In the relational database community, algorithms have been defined to transform a relational schema from one normal form to a more suitable normal form. These algorithms have been shown to preserve certain semantics during the transformation. The work presented in this paper is the first step towards representing such algorithms for semistructured data, namely formally defining the semantics necessary for achieving this goal. Formal semantics and automated reasoning tools enable us to reveal the inconsistencies in a semistructured data model and its instances. The Object Relationship Attribute model for Semistructured data (ORA-SS) is a graphical notation for designing and representing semistructured data. This paper presents a methodology of encoding the semantics of the ORA-SS notation into the Web Ontology Language (OWL) and automatically verifying the semistructured data design using the OWL reasoning tools. Our methodology provides automated consistency checking of an ORA-SS data model at both the schema and instance levels.
10228448
A Z Approach in Validating ORA-SS Data Models
The rapid growth of the World Wide Web has resulted in more data being accessed over the Internet. In turn there is an increase in the use of semistructured data, which plays a crucial role in many web applications particularly with the introduction of XML and its related technologies. This increase in use makes the design of good semistructured data structures essential. The Object Relationship Attribute model for Semistructured data (ORA-SS) is a graphical notation for designing and representing semistructured data. In this paper, we demonstrate an approach to formally validate the ORA-SS data models in order to enhance the correctness of semistructured data design. A mathematical semantics for the ORA-SS notation is defined using the Z formal language, and further validation processes are carried out to check the correctness of the semistructured data models at both the schema and instance levels.
1721253
Object-Z web environment and projections to UML
This paper presents the XML/XSL approach to the development of a web environment for the formal speci cation language Object-Z. The projection techniques and tools from Object-Z (in XML) to UML (in XMI) are developed using XSL Transformations (XSLT). Furthermore, Object-Z (itself) is used to specify and design the essential functionalities of the web environment and the projection tools to UML. In a sense, the paper also demonstrates a formal approach to modeling web applications.
15503932
A tools environment for developing and reasoning about ontologies
Started in the beginning of 2001, the semantic Web is regarded by many as the next generation of the Web. Ontology languages are the building blocks of semantic Web as they provide basic vocabularies for data markups: the ontologies. The correctness of shared ontologies is crucial to the proper functioning of agents. Hence ensuring the consistency of ontologies is a central issue in both the design and deployment phases of any semantic Web-aware application. Our experiences show that semantic Web is a novel and fruitful application domain for formal languages and their mature reasoning tool support. In order to ease the application of formal methods and tools to the semantic Web, we developed an integrated tools environment to support systematic development of OWL ontologies and then transformation, reasoning assistance and querying of them.
2512098
XML-Based Static Type Checking and Dynamic Visualization for TCOZ
Timed Communicating Object Z(TCOZ) combines Object-Z's strengths in modelling complex data and state with TCSP's strengths in modeling real-time concurrency. Based on our previous work on the XML environment for TCOZ, this paper firstly demonstrates the development of a type checker for detecting static semantic errors of the TCOZ specification, then illustrates a transformation tool to automatically project TCOZ models into UML statechart diagrams for visualising the dynamic system behaviour.
15850441
Validating Semistructured Data Using OWL
Semistructured data has become prevalent in both web applications and database systems. This rapid growth in use makes the design of good semistructured data essential. Formal semantics and automated reasoning tools enable us to reveal the inconsistencies in a semistructured data model and its instances. The Object Relationship Attribute model for Semistructured data (ORA-SS) is a graphical notation for designing and representing semistructured data. This paper presents a methodology of encoding the semantics of ORA-SS in the Web Ontology Language (OWL) and automatically validating the semistructured data design using the OWL reasoning tool – RACER. Our methodology provides automated consistency checking of an ORA-SS data model at both the schema and instance levels.
13626429
Local Correlation Tracking in Time Series
We address the problem of capturing and tracking local correlations among time evolving time series. Our approach is based on comparing the local auto-covariance matrices (via their spectral decompositions) of each series and generalizes the notion of linear cross-correlation. In this way, it is possible to concisely capture a wide variety of local patterns or trends. Our method produces a general similarity score, which evolves over time, and accurately reflects the changing relationships. Finally, it can also be estimated incrementally, in a streaming setting. We demonstrate its usefulness, robustness and efficiency on a wide range of real datasets.
17998767
Text Classification Improved through Automatically Extracted Sequences
We propose to use the n-multigram model to help the automatic text classification task. This model could automatically discover the latent semantic sequences contained in the document set of each category. Based on the n-multigram model and the n-gram language model, we put forward two text classification algorithms. The experiments on RCV1 show that our proposed algorithm based on n-multigram model can achieve the similar classification performance compared with the one based on n-gram model. However, the model size of our algorithm is only 4.21% of the latter one. Another proposed algorithm based on the combination of nmultigram model and n-gram model improves the micro- F1 and macro-F1 values by 3.5% and 4.5% respectively which support the validity of our approach.
7323545
Mining clickthrough data for collaborative web search
This paper is to investigate the group behavior patterns of search activities based on Web search history data, i.e., clickthrough data, to boost search performance. We propose a Collaborative Web Search (CWS) framework based on the probabilistic modeling of the co-occurrence relationship among the heterogeneous web objects: users, queries, and Web pages. The CWS framework consists of two steps: (1) a cube-clustering approach is put forward to estimate the semantic cluster structures of the Web objects; (2) Web search activities are conducted by leveraging the probabilistic relations among the estimated cluster structures. Experiments on a real-world clickthrough data set validate the effectiveness of our CWS approach.
1433509
A Distributed Surveillance System to Improve Personal Security in Public Transport
This paper presents a distributed surveillance system to improve safety andsecurity in public transport environments such as metropolitan railways,airports etc. The system is constructed by a set of modules that provideadditional intelligence to detect potentially dangerous situations and providemore timely prevention and management of events. These modules includeCCTV video processing, audio detection, mobile smart cards, a range of otherpossible sensors and a supervisory front-end. The system design uses ideasfrom control engineering and distributed network communication resulting in aCORBA based architecture and XML messaging. The system components havebeen implemented and integrated in two major successful trials in metropolitanrailway stations (London and Paris) and at Newcastle International Airport, aspart of a major EU-funded project PRISMATICA (?PRo-active Integratedsystems for Security Management by Technological, Institutional andCommunication Assistance?).
7495827
Stereo Matching Using Belief Propagation
In this paper, we formulate the stereo matching problem as a Markov network consisting of three coupled Markov random fields (MRF's). These three MRF's model a smooth field for depth/disparity, a line process for depth discontinuity and a binary process for occlusion, respectively. After eliminating the line process and the binary process by introducing two robust functions, we obtain the maximum a posteriori (MAP) estimation in the Markov network by applying a Bayesian belief propagation (BP) algorithm. Furthermore, we extend our basic stereo model to incorporate other visual cues (e.g., image segmentation) that are not modeled in the three MRF's, and again obtain the MAP solution. Experimental results demonstrate that our method outperforms the state-of-art stereo algorithms for most test cases.