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Data interoperability is a prerequisite to achieve cross-community and cross-application sharing of information and knowledge. Heterogeneous data from multiple sources including semantic and non-semantic data sources (e.g. SNS data, web data, relational data, RDF, XML, CSV, etc.) have an important effect for IoT service provisioning. The data are not in a same type or format always that requires to...
With the continuous development of society and the improvement of Internet technology, people are getting more and more dissatisfied with the current exploration of unknown world, and increasingly rigorous on the search engine requirements. As a result, semantic search technology came into being. This article mainly through the knowledge graph and semantic search technology to understand the function...
The inferences of a machine learning algorithm are naturally limited by the available data. In many real-world applications, the provided internal data is domain-specific and we use external background knowledge to derive or add new features. Semantic networks, like linked open data, provide a largely unused treasure trove of background knowledge. This drives a recent surge of interest in unsupervised...
Twitter has become key for bringing awareness about real-world events, but the identification of event related posts goes beyond filtering keywords. Semantic enrichment using knowledge sources such as the Linked Open Data (LOD) cloud, has been proposed to deal with the poor textual contents of tweets for event classification. However, each work considers a particular type of event, underlined by specific...
Probabilistic topic models are powerful techniques which are widely used for discovering topics or semantic content from a large collection of documents. However, because topic models are entirely unsupervised, they may lead to topics that are not understandable in applications. Recently, several knowledge-based topic models have been proposed which primarily use word-level domain knowledge in the...
Even the best performing object tracking algorithm on well known datasets, commits several errors that prevent a concrete adoption in real case scenarios unless you do not accept some compromise about tracking quality and reliability. The aim of this paper is to demonstrate that adding to a traditional object tracking solution a knowledge based reasoner build on top of semantic web technologies, it...
With the rapid growth of semantic data, scalable reasoning has attracted more, more attention. However, most existing works about scalable reasoning focus only on RDFS/OWL ter Horst semantics, which are small fragments of OWL 2 RL,, have limitation in expressivity. As OWL 2 RL semantics extended with SWRL rules can be expressed by datalog language, materialization of datalog programs is widely adopted...
In this paper, we present a semantic web based knowledge engineering approach to extend the coverage of medical knowledge-based systems in order to solve complex medical queries that demand the integration of deterministic and plausible knowledge. We leverage plausible reasoning mechanisms, which exploit associations between the underlying domain-specific data, as well as tentative domain knowledge,...
Inconsistencies in real world knowledge bases are very common because the knowledge bases are usually authored at multiple places on the Web. These inconsistencies are even carried over to local closed world reasoning (LCWR) where the knowledge base consists of open world assumption (OWA) predicates (concepts or roles) and closed world assumption (CWA) predicates. When data from a relational database...
The World Wide Web connects a wide variety of communities in medical domain, and provides a platform for knowledge exchange and integration between Traditional Chinese Medicine (TCM) and biomedicine. However, the cultural gaps between TCM and Western Medicine hinder cross-cultural communication. We utilize Semantic Web technologies to build a knowledge base that integrates distributed and heterogeneous...
Semantic annotation plays an important role for semantic-aware web service discovery, recommendation and composition. In recent years, many approaches and tools have emerged to assist in semantic annotation creation and analysis. However, the Quality of Semantic Annotation (QoSA) is largely overlooked despite of its significant impact on the effectiveness of semantic-aware solutions. Moreover, improving...
In the modern era numerous information are available in the World Wide Web which makes it difficult to get the semantic information. Ontologies plays vital role after the evolution of the Semantic Web. Ontologies are used in various domains. Ontology is used to refine the search with semantics and give the best result to the user. This paper portrays the construction of two different domain ontologies...
Community Health Workers (CHWs) act as liaisons between health-care providers and patients in underserved or un-served areas. However, the lack of information sharing and training support impedes the effectiveness of CHWs and their ability to correctly diagnose patients. In this paper, we propose and describe a system for mobile and wearable computing devices called Rafiki which assists CHWs in decision...
It can be foreseen that the volume of ontology's Abox in Semantic Web of Things is always too large to understand or reason about ontology by machines and users. To solve this problem, a SWoT ontology summarization method based on equivalence relation is proposed, and a system based on this method is designed and implemented. Some experimental result analyses show that this method not only can reserve...
Popular techniques used in today's Web search engines and digital libraries for retrieving and ranking scientific publications have foundations in modern information retrieval. Information and users in the scientific research communities have their own characteristics, however, they have not been sufficiently exploited in existing retrieval and ranking methods. We present a semantic search engine,...
Twitter has became an invaluable source of information, due to his dynamic nature with more than 400 million tweets posted per day. Determining what an individual post is about can be a non trivial task because his high contextualization and his informal nature. Named Entity Linking (NEL) is a subtask of information extraction that aims to ground entity mentions to their corresponding node in a Knowledge...
Ontologies are an essential component of the Semantic Web and in recent times, the significance of modular ontologies is largely increasing due to their superiority over monolithic ontologies. Out of the multiple modularization choices available, the one which guarantees best system design and performance should be applied. Some attributes of modular structure such as cohesion and coupling, determine...
Information security contains many concepts and knowledge entities. As the development of information technology, the complexity of increasing information security knowledge need an overview representation and organization for security analysis and risk evaluation. Ontology as a formal and shareable semantic model, which is often used to define domain knowledge schema, can also be applied for information...
The Semantic Web is an extension of the current World Wide Web, and aims to help computers to understand and process web information automatically. In recent years, the integration ontologies and rules has become a central topic in the Semantic Web. Therefore, significant research efforts have focused on integration description logic programs. However, description logic programs cannot well model...
Innovative analysis methods applied to data extracted by off-the-shelf peripherals can provide useful results in activity recognition without requiring large computational resources. In this paper a framework is proposed for automated posture and gesture recognition, exploiting depth data provided by a commercial tracking device. The detection problem is handled as a semantic-based resource discovery...
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