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One of the main research problems in heterogeneous transfer learning is to determine whether a given source domain is effective in transferring knowledge to a target domain, and then to determine how much of the knowledge should be transferred from a source domain to a target domain. The main objective of this paper is to solve this problem by evaluating the relatedness among given domains through...
Analysis modeling refers to the task of identifying domain objects, their attributes and operations, and the relationships between these objects from software requirements specifications which are usually written in some natural language. There have been a few efforts to automate this task, but they seem to be largely constrained by the language related issues as well as the lack of a systematic transformation...
Process models describe graphically, events, activities, control flow and dataflow logic that constitute a business process. Nevertheless most graphical modeling notations required by organization stakeholders such as BPMN, are not provided with a formal semantics, limiting the possibility of analysis to informal approaches such as observation techniques. While most of the existing formal approaches...
In this paper, we show a System Self-Awareness concept and theory that can be used to discover authoritative and popular information as well as emerging and anomalous information when traditional connections among information nodes (e.g., hyperlinks or citations) are not available. The different categories of information can be all high-value depending on the application requirements. A System Self-Awareness...
Today's dominant RTL languages, VHDL and (System) Verilog, were designed as description and simulation languages. Therefore, they have a clearly defined - but not in all cases deterministic - simulation algorithm as backbone of the language definition. Both languages have been adopted as RTL design languages but still impose a lot of simulation/synthesis mismatches. As a further disadvantage, considerable...
Concerning intelligent information and analytical systems one of the most prospective areas is the construction of knowledge bases used ontological systematization as a tool for classification of corporate knowledge. The authors interpret a competence model, which can select significant features of classifiable objects, in terms of domain ontology. To classify corporate objects it is suggested a heuristic...
The paper proposes the syntax-oriented processing (analysis, checking and translation) methods of diagrammatic models in the design of complex automated systems. The methods are based on the author's finite-state graphical grammar.
The article is devoted to setting objectives and developing ways to solve problems of knowledge semantic search, classification, structuring and integration in relation to knowledge management issue. Information management is viewed as a set of processes systematic acquisition, synthesis and sharing of knowledge. Knowledge management automation problem as continuous knowledge verification process...
Syntactic text analysis is a very important step of automatic text processing. The key problem is that all existing approaches are dictionary-dependent. It can be impossible to analyze all sentences because of the lack of one word in the dictionary. However even the presence of the dictionary does not resolve the phrases interpretation ambiguity. At the same time fusional languages contain enough...
A questionnaire text mining model is built based on latent semantic analysis (LSA). Take open questionnaire as the research object and improve Latent Dirichlet Allocation (LDA) model according to the text characteristics, a BM25-LDA model is built. By comparing the LDA model and BM25-LDA model on the open questionnaire text, we can verify that the performance of BM25-LDA mode is better than that of...
3D digital city models form the basis for flow simulations (e.g. wind flow and water runoff), urban planning, under-and over-ground formation analysis, and they are very important for automated anomaly detection on man made structures. They consist of large collections of semantically rich objects which have many properties such as material and color. Such user's data structure perception is leading...
This paper describes an ontology driven framework for collaborative information analysis and knowledge discovery. The framework, called Semantic Technology for Evidence Exploration and Learning (STEEL), includes a collection of methods and an architecture that implements the method. The framework includes methods for collaborative visual analytics, workflow automation mechanisms, an automation support...
Criminal Intelligence Analysis often requires a search different from the semantic and keyword based searching to reveal the associations among semantically and operationally connected objects within a crime knowledge base. In this paper we introduce associative search as a search along the networks of association between objects like people, places, other organizations, products, events, services,...
Response time plays an important factor in determining the Service Level Agreement (SLA). For the reason that actual measurement costs a large amount of resource, theoretical/numerical analysis based on Stochastic Process Algebra (SPA) is a good choice to obtain the response time of concurrent systems. Among all SPAs, Performance Evaluation Process Algebra (PEPA) is the most popular one due to its...
Evacuation management related problems involves multidisciplinary response tasks. Integrate decision support demands for intelligent management, collaboration and visualization of multiple model and data resources in distributed and heterogeneous environment. In this paper, a service-oriented distributed architecture is developed for integrated decision support in emergency evacuation management....
Real Time Bidding (RTB) is an emerging business model and a popular research topic of online advertising markets. Using cookie-based big-data analysis, RTB advertising platforms have the ability to precisely identify the features and preferences of online users, segment them into various kinds of niche markets, and thus achieve the precision marketing via delivering advertisements to the best-matched...
The article reviews the formalization of structural-syntactic approach in terms of identifying-structural control with the use of structural representation of complex systems. The traditional practice of systemic approach is complemented with the approach to solving the problems of description and analysis of the unity of elements for identifying structures and substructures. The structural approach...
Probabilistic topic models are powerful techniques which are widely used for discovering topics or semantic content from a large collection of documents. However, because topic models are entirely unsupervised, they may lead to topics that are not understandable in applications. Recently, several knowledge-based topic models have been proposed which primarily use word-level domain knowledge in the...
This paper is part of a doctoral thesis that aims to propose an evaluation model, for later application, using Educational Data Mining techniques to analyze the responses of students obtained during an Institutional Teaching Evaluation. Therefore, the authors propose an Institutional Teaching Evaluation model that applies, among others, the Sentiment Analysis to identify which teaching practices are...
Knowledge and experience of a case manager re- mains a key success factor for Case Management Processes (CMPs). When a number of influential parameters is high, a number of possible scenarios grows significantly. Automated guidance in scenario evaluation and activity planning would be of a great help. In our previous work, we defined the statecharts semantics for visualisation and simulation of CMP...
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