Structured prediction has been successfully applied to problems with strong interdependencies among output variables. In the realm of natural language processing (NLP), various tasks are formulated into structured prediction problems. Exist exact inference methods for sequences and trees. For tasks with general output structures, e.g., the pairwise fully connected undirected graph, the exact inference problem […]
Cluster consensus in discrete-time networks of multi-agents with inter-cluster nonidentical inputs
The multi-agent systems have broad applications. The consensus problems of multi-agent systems have attracted increasing interests from many fields, such as physics, control engineering, and biology. In network of agents, consensus means that all agents will converge to some common state. A consensus algorithm is an interaction rule how agents update their states. The consensus […]
A Quantitative Approach to Input Generation in Real-Time Testing of Stochastic Systems
The testing process, an implementation is exercised under controlled conditions with the intent of observing deviations with respect to the expected behavior. The development of reactive and real-time systems, this often relies on the execution of test-suites derived from abstractions that focus on finite-state and timed behavior, with the aim of revealing defects related to […]
Predicate in Euclidean space and road networks
A large amount of data is an important operation in a wide range of domains. Felipe et al. has recently extended its study to spatial databases, where keyword search becomes a fundamental building block for an increasing number of real-world applications, and proposed the IR2-Tree. A main limitation of the IR2-Tree is that it only […]
Safe and preserve personalization in module-based data management
In many application domains (e.g., medicine or biology), comprehensive schemas resulting from collaborative initiatives are made available. For instance, SNOMED is an ontological schema containing more than 400.000 concept names covering various areas such as anatomy, diseases, medication, and even geographic locations. Such well-established schemas are often associated with reliable data that have been carefully […]
Prevent re-identification attacks by adversaries with immediate neighborhood structural knowledge
The publication of social network data entails a privacy threat for their users. Sensitive information about users of the social networks should be protected. The challenge is to devise methods to publish social network data in a form that affords utility without compromising privacy. Previous research has proposed various privacy models with the corresponding protection […]
Ontology- Language based in multi -facet (OMF) framework
The last decade, there has been tremendous growth in the field of network. The information served to the internet users through web is enormous. Some information provided is of use to the end users, and others of no use to them. Current web information gathering systems attempt to satisfy user requirements by capturing their information […]
ANALYZING DATA ANALYSIS TASKS UNDER THE DNCC MODEL
Privacy and security, particularly maintaining confidentiality of data, have become a challenging issue with advances in information and communication technology. The ability to communicate and share data has many benefits, and the idea of an omniscient data source carries great value to research and building accurate data analysis models. For credit card companies to build […]
METRIC AND MATHEMEDICAL FOR EVALUATING NAVIGATION EFFECTIVENES
The advent of the Internet has provided an unprecedented platform for people to acquire knowledge and explore information. There are 1.73 billion Internet users worldwide as of September 2009, an increase of 18 percent since 2008 .The fast-growing number of Internet users also presents huge business opportunities to firms. the increasing demands from online customers, […]
Social science and energy efficiency instantiation human behavior modeling
One seeks to develop predictive models to map between a set of predictor variables and an outcome. Statistical tools such as multiple regression or neural networks provide mature methods for computing model parameters when the set of predictive covariates and the model structure are pre-specified. Recent research is providing new tools for inferring the structural […]
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