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This paper puts forward a knowledge push method which is based on multidimensional hierarchical context model for general business process, and constructs a multi-dimensional hierarchical model of business process and a context driven knowledge resource database model, which emphasizes the mapping relation between knowledge and the knowledge context. On this basis, a framework of the knowledge push...
Knowledge-intensive business services (KIBS) such as management consulting, research and development, and IT outsourcing, have become a key component of most industrialized economies. As such, there has been a growing number of empirical studies investigating the way in which KIBS providers, clients, and partners collaboratively create value. These studies provide an important opportunity to improve...
In modern military operations the emphasis is on smaller teams and more ad hoc teamwork. This requires greater agility both in terms of capturing actionable intelligence as well as appropriate dissemination and fusion of that information to coalition team members based on their tasks and need to know. In previous research and development we have explored the potential for a controlled natural language...
Context-aware systems perform adaptive changes in several ways. One way is for the system developers to encompass all possible context changes in a context-aware application and embed them into the system. However, this may not suit situations where the system encounters unknown contexts. In such cases, system inferences and adaptive learning are used whereby the system executes one action and evaluates...
Highly expressive declarative languages, such as Datalog, are now commonly used to model the operational logic of data-intensive applications. The typical complexity of such Datalog programs, and the large volume of data that they process, call for the tracking and presentation of data provenance. Provenance information is crucial for explaining and justifying the Datalog program results. However,...
Intelligent Systems are envisaged to share some or all of the work of heavily burdened human experts in the domain of health, education, social security, forecasting, engineering, agriculture, eco balance, investment, law, etc. Moreover, since the life of a human is very precious, and wherever chances of fatality is very high, all those endeavors are thought of to be handed over to an intelligent...
Repairing an inconsistent knowledge base is a well known problem for which several solutions have been proposed and implemented in the past. In this paper, we start by looking at databases with active integrity constraints - consistency requirements that also indicate how the database should be updated when they are not met - as introduced by Caroprese et al.We show that the different kinds of repairs...
The evolution simulation is a popular problem not only in biology but in the computer science as well. This paper will introduce the principles of the evolution units. An artificial organism, a digital evolutionary machine (DEM) will be constructed based on these principles. Properties and abilities of DEMs will be shown with resolved and pending questions. After the theoretical approach some experimental...
The theories of concept lattice expansion and recovery were presented in this paper. Firstly, a formal context can be reduced from the viewpoint of objects or attributes by inclusion reduction, and its corresponding concept lattice can be constructed. And then, the concept lattice can be expanded dynamically according to the need, thus, the concept lattice of original formal context can be recovered...
We address the problem of combining information from diversified sources in a coherent fashion. A generalized evidence processing theory and an architecture for data fusion that accommodates diversified sources of information are presented. Different levels at which data fusion may take place such as the level of dynamics, the level of attributes, and the level of evidence are discussed. A multi-level...
Foreign students who live and study in China encounter many problems in Chinese language learning, as language learning often correlates with background knowledge which varies from country to country caused by cultural and social differences in terms of distinct public policies and services. With the increasing number of foreign students in China and the great demand for mobile Chinese language learning...
A problem of diversified entity summarisation in RDF-like knowledge graphs, with limited ??presentation budget??, is formulated and studied. A greedy algorithm that adapts previous ideas from IR is proposed and preliminary but promising experimental results on real dataset extracted from IMDB database are presented.
The ever more widespread use of the Web for knowledge sharing has led to the creation of a wide spectrum of opportunities for employing shared information resources and, at the same time, a gradual increase in the technologies for making these resources available. In this scenario, it is important to define new methods and techniques that can support users' search activities and selection of the resources...
In this paper, we report on an implemented rule-based tool for grapheme to phoneme conversion for the Romanian language and experiments run on two different sets of words. A 4779 words database consisting of the most frequent words in a text corpus collected from 93 books representing genuine Romanian literature, foreign literary works translated into Romanian and scientific texts was transcribed...
Word sense disambiguation (WSD) is the core and one of the hardest problems of many natural language processing tasks. WSD is considered as an AI-complete problem. Although there are many approaches trying to solve this problem, many of them are not adequate to solve WSD problem for Turkish. Dealing with sense ambiguity for Turkish also requires dealing with stemming ambiguity as well as polysemy,...
With the quick development of economy, the market changes so rapidly that the business logics are forced to change frequently. In an original real-time financial system, the cost of maintenance was very high since the business logics were mixed up with the code at application level. This paper elaborated a kind of rule engine implementation mode for the financial system. The rule engine separated...
In this work we present "AlertMe", a semantics-based, context-aware notification system that provides personalized alerts to graduate students based on their preferences. An extensive description of the system is carried out. We present the underlying ontology that models the available knowledge, as well as how higher level knowledge inference and context-based decision making is achieved...
This paper describes a knowledge-based collaboration environment for ITIL which is aimed at making work of IT consultants dealing with planning, designing and implementing ITIL processes easier. The collaboration environment organizes work of consultants around built-in ITIL concepts and allows them to map and refine concepts for a particular customer engagement. The collaboration environment is designed...
Exception handling is an important issue in service composition domain, and its mechanism should be considered in the service composition process. When invoking the composite service, exception handling involves with not only process design and status, but also service execution status. This paper proposes a context-sensitive ECA Rule based approach to analyze composite service exception (ANALEPTIC),...
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