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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...
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...
This paper summarizes results on a recently introduced family of Datalog-based languages, called Datalog+/-, which is a new framework for tractable ontology querying, and for a variety of other applications. Datalog+/- extends plain Datalog by features such as existentially quantified rule heads and, at the same time, restricts the rule syntax so as to achieve decidability and tractability. In particular,...
Semantic Web applications meet a serious problem in practice: the shortage of semantic data (ontologies). Since the vast majority of data are still stored in relational databases, they are unavailable for the most next generation Web applications, such as Semantic Digital Libraries. Therefore, it becomes one of core challenges of Semantic Web whether applications can automatically retrieve semantic...
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 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...
The purpose of the present work was to create a computational framework for radiological registry and diagnosis, which, by means of a nonintrusive approach, allows the users freedom annotation while storing related information in a structured and standard format. To get this goal, this work started with the investigation of lexical and semantic domain of radiological texts, followed by the design...
With the rapid development of information technology, huge data is accumulated. A vast amount of such data appears as short messages such as emails in companies or conversations in open chatting rooms. It is useful to find the themes or exceptional information from the messages by clustering the short documents based on density. However, traditional vector space model based text clustering algorithms...
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...
Despite the critical importance of semantic interoperability between heterogeneous databases, current approaches have not been sufficiently effective and comprehensive. We propose an ontology-based solution, which use two kinds of ontologies called schema-level conflict ontology and data-level conflict ontology (SLCO and DLCO). SLCO and DLCO are two ontologies for detecting and resolving schema and...
We present a semantic context management framework named Context Torrent, which can make various types of context information be semantically searchable and sharable among local and remote context-aware applications. We implement this framework on the Google Android platform with its elegant application support. An open source RDF parser has been extended to effectively get RDF triples from files...
This article presents a concept model, and the associated tool to help advanced learners to find adapted bibliography. The purpose is the use of an IT representation as educational research software for newcomers in research. We use an ontology based on the ACM's Computing Classification System in order to find scientific articles directly related to the new researcher's domain without any formal...
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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