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In order to secure vital personal and organizational system we require timely intelligence on cybersecurity threats and vulnerabilities. Intelligence about these threats is generally available in both overt and covert sources like the National Vulnerability Database, CERT alerts, blog posts, social media, and dark web resources. Intelligence updates about cybersecurity can be viewed as temporal events...
The user profile is a way of describing user characteristics using collected information about what the user prefers. However, it cannot be used for other applications with a general purpose, because it is generally created for personal recommendation and search. Furthermore, there are restrictions to analyze the user profile in terms of temporal influence in mobile environments. In this paper, in...
Application of attribute-oriented generalization to an informatation often lead to inconsistent results of rule induction, which can be viewed as generation of fuziness with partialization of attribute information. This paper focuses on fuzzy linguistic variables and proposes a solution for inconsistencies. The results show that domain ontology may play an important role in construction of linguistic...
User annotation of images has become a popular solution for image classification and retrieval. This paper reports a machine learning approach in taxonomy induction that applies image annotations involved in different levels of meaning making from the participants. Results of the study indicate the effectiveness of the method. The study suggests that the discussed machine learning procedures can be...
To assist decision makers, there is need of providing an insight on current of scenario of market, considering really sensitive news involving economic events like acquisitions, stock splits, or dividend announcements. Similar to the work discussed above, to machine process natural language constraints, there is need of a mechanism that can automate events related information extraction and knowledge...
In recent years homeland security is becoming increasingly sensitive to threats posed by the tactics of subversive groups or individuals with malicious intent. Networked groups and organizations leverage various means of communication, ranging from simple phone calls to more sophisticated forms of collaborations. Such data provide a rich collection of evidence from which to infer relationships of...
Achieving space domain awareness requires the identification, characterization, and tracking of space objects. Storing and leveraging associated space object data for purposes such as hostile threat assessment, object identification, and collision prediction and avoidance present further challenges. Space objects are characterized according to a variety of parameters including their identifiers, design...
In decision tasks such as bioprocess efficiency comparison, scientific literature is a valuable source of data. This large number of scientific data is heterogeneously structured, mainly in textual format. Innovative tools able to integrate and treat constantly new information are required. In this context, the use of semantic web methods such as ontologies seems relevant to structure the experimental...
Medical Information Retrieval (IR) aims to extract relevant medical information from the web, patients' records, electronic books, research articles etc. However, users are generally unfamiliar with medical terms and find difficulties expressing their needs. One interesting solution is to integrate fuzzy ontologies in order to achieve semantic interoperability and offer a way to handle vague and imprecise...
One important goal of computer science, complete simulation of human has been achieved through cloud computing, big data and artificial intelligence with machine learning. Process of situation awareness consists of (1) Perception to obtain necessary information (2) Comprehension of situation to identify facts for capturing situation (3) Projection to infer proper reaction to the situation. The task...
Publishing individual-related data for big data analysis such as scientific research and merchant analysis has become frequent in this decade. Most of these data can be represented as graphs, with real world entities as graph nodes and interrelationships among entities as graph edges. Mining these released data, or corresponding graphs, may facilitate the forming of judicious strategies for marketing...
Urban Data management represents a major challenge in the field of Smart Cities. Its understanding is essential for the development of better smart services, which are a persistent demand in urban policies. From all the sources of data available, those that involve a collective processing of urban information (by the citizens or other collectives) deliver in fact, useful insights into social perception...
Many software systems nowadays aim for usability or accessibility from the effectiveness and ergonomics point of view. However, there still is lack of such ones that correctly use the domain dictionary, correctly describe domain relations and properties and implement the target domain processes via their user interfaces. This property is called ‘domain usability’. In this paper we describe the state...
This paper presents a context-aware ontological approach applied to an alarm management system. The goal is to easier the work of the plant's operators using supervisory systems and process control. Being part of a Supervisory Control and Data Acquisition (SCADA), alarm management systems produces and stores a big data set. Using proper analysis techniques in order to produce information and knowledge...
One of the biggest challenges in Big Data is to exploit value from large volumes of variable and changing data. For this, one must focus on analyzing the data in these Big Data sources and classify the data items according to a domain model (e.g. an ontology). To automatically classify unstructured text documents according to an ontology, a hierarchical multi-label classification process called Semantic...
The domain model is an essential part of an adaptive learning system. For each educational course, it involves educational content and semantics, which is also viewed as a form of conceptual metadata about educational content. Due to the size of a domain model, manual domain model creation is a challenging and demanding task for teachers or content (and metadata) authors. We propose a method for the...
The Museum of the Person (Museu da Pessoa, MP) is a virtual museum aimed at exhibiting life stories of common people. Its assets are composed of several interviews involving people whose stories we want to perpetuate. So the museum holds an heterogeneous collection of XML (eXtensible Markup Language) documents that constitute the working repository. The main idea is to extract automatically the information...
High-quality inquiry (i.e. history taking) is the foundation of accurate diagnosis. Traditionally, inquiry occurs between doctors and patients, requiring lots of time and patience, but often receiving a lot of complaints. This paper proposes a smart inquiry framework, aiming for interacting with patient readily by mining personalized questions from biomedical big data. In other words, the patient...
The first W3 Consortium standard to represent metadata with rich amount of information resource of the web is referred as Resource Description Framework (RDF). RDF semantic web approaches are used on different areas of research today such as social network analysis, discovering semantic associations, semantic web engineering and so on. Social networking in modern society is a communication mechanism...
Data retrieval is a key process of acquiring information as per requirement. Now days, the necessity of proper information has increased. The most basic tools which provide this service are browser. It traverses the data as per user's query and gives the search results of all related information. Hence, it becomes a time consuming process to find required information. In this paper, the focus is done...
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