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There are some independent cyber security knowledge bases for different aspect now. In the internet, there is also much cyber security related content which exists in the form of text. Fusion of these cyber security related information can be a meaningful work. In this paper, we propose a framework to integrate existing cyber security knowledge base and extract cyber security related information from...
The current state of affairs regarding the way events are logged by IT systems is the source of many problems for the developers of Intrusion Detection Systems (IDS) and Security Information and Event Management (SIEM) systems. These problems stand in the way of the development of more accurate security solutions that draw their results from the data included within the logs they process. This is...
Every research field (domain) has a lot of data or information in textual format. The main problem is how to optimally arrange and transform the textual data or information to explore research issues. The authors propose a framework that may help in exploration of research issues from text of specific field (domain). First textual data or information is transformed to semantic network by using some...
Cerebrovascular diseases are one of the most common causes of death worldwide. In this paper, we analyze relationships in heterogeneous collaborating centre's medical data to resolve a solution of this complex problem. Data mining is primarily based on clinical data, imaging examinations and therapeutic data stored in various data formats. The raw and mined data can be used by a registered medical...
As e-mail usage increases and its volume and size becomes unpredictable, there is a dire need to have richer email clients with increased ease of use. Ease of use continues to be the most significant success factor in e-mail usage. In this paper we introduce scalable features that primarily address ease of use when e-mail volume increases unprecedentedly. One feature relates to graphical e-mail content...
This paper presents a method for integrating DBpedia data into an ontology learning system that automatically suggests labels for relations in domain ontologies based on large corpora of unstructured text. The method extracts and aggregates verb vectors for semantic relations identified in the corpus. It composes a knowledge base which consists of (i) centroids for known relations between domain concepts,...
In order to improve the performance of KDD greatly, the paper researched KDD model process based on double bases cooperating mechanism and focused on one of its part that is heuristic coordinator, which simulated the creating intent of cognitive psychology feature. And an improved heuristic coordinator algorithm was proposed. The method used FCM representing knowledge and being effective inference...
In semantic Web, ontology mapping is the basis of the interoperation of heterogeneous ontologies. Ontologies are usually distributed and heterogeneous and thus it is necessary to find the mapping between them before processing across them. The current ontology mapping methods merely use massive Web pages in the Internet and they are unpractical to subsequent interoperation and integration of heterogeneous...
In order to prevent and reduce coal mine gas explosion occurred, this paper firstly generally designed pre-warning expert system of coal mine gas safety which based on object-oriented. Secondly, it developed and realized the function of the system, including the establishment of a comprehensive database and knowledge base, the information in the system can more accurately be expressed through the...
This paper firstly inquired the categories of knowledge on dam safety monitoring expert system and the knowledge acquisition process. Secondly, it not only analyzed knowledge representation about dam safety monitoring expert system, that is, factual knowledge, rule knowledge and procedure knowledge, but also established a simple knowledge base based on relational database for dam safety monitoring...
To overcome the shortcomings of traditional search engines with the limitation to the retrieval of lists of potentially relevant document, an ontology-based intelligent search engine, called CRAB, aims to deploy natural language tools to automatically extract knowledge from Web documents and effectively manage RDF triples in a given knowledge base by an OWL DL reasoner, which is used to check the...
Both expert system and data mining belong to the Artificial Intelligence fields. Association rule is a method of datamining, whose typical application is analyzing the shopping basket in supermarket. The main task of expert system is ratiocination, while that of association rule is to find out the valuable relationship between each data item. By modifying the apriori arithmetic and the method of the...
Sem@ntica is a system for extracting the information contained in collections of documents into a knowledge base. It combines high quality conventional named entity analysis with an ontology class labeling capability for open class words. The ontology comprises an upper ontology and one or more domain ontologies. The system has tools for rapidly designing the ontology and mapping segments of Word...
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