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The main problem of rule-based information extraction technique is that the extraction rules tend to be specifically designed for specific information or document structure; hence it cannot be directly used in another without some proper modifications. Semi-structured documents like tables present another challenge to information extraction; since there are no standards on how to design it, the structure...
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...
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...
In the context of large engineering projects the effective and efficient exchange and versioning of information from different engineering disciplines is essential. Semantic data integration approaches provide the necessary means to overcome the gap between heterogeneous local engineering tool concepts and common project-level concepts which enable the mapping of engineering data coming from different...
Big Data Era brings two main dimensions, which are heterogeneity and contextual data. The heterogeneity may occur at syntax and semantic levels. Ontologies are largely used to reduce these heterogeneities. Data has limited value if not paired with its context. Usually the internal data of companies are not connected to the rest of data universe including news, weather, user profiles, etc. In Engineering...
Trust and quality maintenance have always been problematic in the Semantic Web RDF bases. Numerous propositions to address these problems of data integration have been made, either based on ontologies or on additional metadata. However ontologies suffer from a adaptation speed slower than the data evolution speed and metadata requires ad-hoc manipulations of data by addition of extra-data. In this...
This paper presents the implementation of an efficient retrieval system for medical images. By combining ontology with the use of low level feature extraction we were able to retrieve meaningful information from the knowledge base. We also successfully bridged the gap between the low level feature and the high level semantics by applying the image processing technique to extract the low level features...
Data-oriented applications have experienced a huge growth mainly in distributed settings. The increasing amount of available data has made it hard for users to find the information they need in the way they consider relevant. To help matters, a user-centric approach may be used to enhance query answering and, particularly, provide query personalization. In this work, we address the issue of personalizing...
Knowledge Discovery in Databases (KDD) is a highly complex, iterative and interactive process involving several types of knowledge and expertise. In this paper we propose to support users of a multi-view analysis (a KDD process held by several experts with different viewpoints). Our objective is to enhance both reusability of the process and coordination between experts. To do so, we propose a formalization...
In the past few years, there has been an explosive growth in scientific and legal information related to the patent system. Patents and related documents are siloed into multiple heterogeneous sources. Retrieving relevant information from diverse sources is a non-trivial task and poses many technical challenges. Among the challenges is the issue of terminological inconsistencies that are used in the...
The size of the publicly indexable World Wide Web (WWW) has probably surpassed 14.3 billion documents and as yet growth shows no sign of leveling off. Search engines encounter the problem of ambiguity in words; therefore, search engines use ontology to find pages with words that are syntactically different but semantically similar. The knowledge provided by ontology is extremely useful in defining...
The XML DOM (Document Object Model) provides a logical view of the in-memory structure. It represents the metadata that has a hierarchical treelike structure consisting of nodes. There are several benefits of implementing the XML DOM as a home management server. First of all, the process time decreases by three times in average sense than using general database. Secondly, it would make to meet with...
In this paper, we propose a new approach that makes the viewpoint notion explicit in a multiview Knowledge Discovery in Databases (KDD) process. We define a viewpoint in KDD as an analyst's perception of a KDD process, which refers to his own knowledge. Our purpose is to facilitate both the reusability and adaptability of a KDD process, and to reduce its complexity whilst maintaining the trace of...
Recent developments in computer science and networking technologies motivate new families of applications that are sensitive to user and ambient contexts. The objective is to offer adaptive services that can be personalized to users' needs within heterogeneous, complex and dynamic environments. This requires enhanced and generic solutions for context representation and retrieval as well as for the...
In order to provide context-aware services, context modeling is one of the most important tasks. Ontology has been widely accepted for the context modeling but it brings some overheads in the process of reasoning large-scale and dynamic information. In mobile networks, especially, ontology should be verified to be applicable for Context-aware Services since real-time responsiveness for large scale...
For the majority college students in Taiwan, learning and using terminologies of a specific domain between Chinese and English interchangeably are quite a challenge. Most of the students seek for assistances from library resources or search for answers on web. Unfortunately, the students would not be able to identify the correctness of their findings, or the worse, the students cannot choose the right...
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...
The ability to provide both rich and natural answers with respect to a given question, and clear explanations for failures, is a crucial aspect for a future generation of question answering systems able to interact with a user. We argue that such abilities are necessarily based on a deep analysis of the content of both the question and the answer, and propose an ontology-based approach to represent...
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...
In this paper, we propose a characterization of the main classes contained in the database of the system K-DSS and related to the domain of identification of the crucial knowledge for which a capitalizing operation is required. We exploit ontological categories existing in the literature to define the notions of knowledge, actor, support and criteria of knowledge vulnerability. The objective is to...
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