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User Activity Recognition through Software Sensors
Published in Qurban A. Memon, Distributed Networks, 2017
Stephan Reiff-Marganiec, Kamran Taj Pathan, Yi Hong
What has crystallised over the last decade is that ontology-based approaches for context modelling are very promising as they offer the needed structure, while providing ease of extensibility and reusability. All this is provided at a level of formality open to reasoning while still providing simplicity offering a good understanding of the models. There are a number of standard languages for defining ontologies, predominantly OWL, which provide ready access to tools and also readily tie in with web services (in fact, research on semantic web services uses OWL at its heart to introduce semantics to what are otherwise just syntactically described services).
Ontologies for Knowledge Representation
Published in Archana Patel, Narayan C. Debnath, Bharat Bhushan, Semantic Web Technologies, 2023
Knowledge representation is done in the most efficient way when ontologies take the leading role. Knowledge discovery applications are widely used where end-users write complex search requests to retrieve information. These users may not be able to grasp the semantic relationship between the data stored. Such a difficulty can be overcome by representing the knowledge and interactive queries using ontologies. Like any other technology evolving today developing semantic web, technology is also being motivated and benefitted by several opportunities including Semantic web services: Semantic web services are built around universal standards for the interchange of semantic data, which makes it easy for programmers to combine data from different sources and services without losing meaning. Semantic web services can also be used by automatic programs that run without any connection to a web browser. The semantic descriptions are registered in public registries that help the intelligent agents to migrate from one service registry to another and find required web services for the user.Semantic search engines: With the initiation of the Semantic Web, the resources on the Web are represented semantically using ontologies, and search engines can be built where queries can be executed within the context of some ontology. Swoogle is an example of a semantic web search engine for ontologies and documents saved on the web in the form of RDF and RDFS. It uses a collection of crawlers to discover the RDF and HTML documents [42].
Semantic Complex Service Composition within an IoT Ecosystem
Published in Ricardo Armentano, Robin Singh Bhadoria, Parag Chatterjee, Ganesh Chandra Deka, The Internet of Things, 2017
Grigorios Tzortzis, Charilaos Akasiadis, Evaggelos Spyrou
It is well known that orchestrating a collective functionality using highly heterogeneous devices and modules exposed as web services is quite a difficult task. To obtain a comprehensive representation of web services and improve interoperability in the context of IoT so that tasks such as service discovery and composition can be performed in a more effective and efficient manner, semantics are employed to enhance the description of services. Several ontologies have been proposed for adding semantic content to web services, thus transforming them into semantic web services (McIlraith et al., 2001). OWL-S (Martin et al., 2004) and WSMO (Roman et al., 2005) are two renowned efforts, which provide highly expressive models for annotating web services in heterogeneous domains. Rich conceptual approaches, such as OWL-S and WSMO, demand considerable user effort to comprehend them and appropriately annotate the services, whereas reasoning becomes a computationally intensive process. Lately, a tendency has emerged to switch to lightweight semantic models that focus only on the core semantics of web services, trading expressivity for improved usability and complexity. SAWSDL (Kopecký et al., 2007) and WSMO-Lite (Vitvar et al., 2008), which builds upon SAWSDL, are two such examples that allow semantic annotations to be directly added to the WSDL description of services. Accordingly, for RESTful services, hRESTS (Kopecký et al., 2008) and MicroWSMO (Roman et al., 2015), which is based on hRESTS, have been developed, supporting the addition of semantics directly on the HTML description of services. The Minimal Service Model (MSM) (Pedrinaci et al., 2010) is another such approach that provides a common conceptual model for capturing semantics of services, whether they are WSDL based or REST based. As noted by Pedrinaci et al. (2010), MSM is largely compatible with OWL-S and WSMO service models. MSM has been incorporated in the iServe platform (Pedrinaci et al., 2010), a service publication and discovery platform.
Recent Advancements in Semantic Web Service Selection
Published in IETE Journal of Research, 2022
Riddhi Pahariya, Lalit Purohit
In the past decade, tremendous work has been done in semantic web service selection. Researchers have given numerous approaches to strengthen the efficiency and accuracy of semantic web service selection. In the semantic web, web service selection refers to finding the most relevant web service(s) from the enormous available web services with the help of semantics. In semantic web service selection, the process of maximum matching plays an important role. Here, maximum matching refers to the maximum possible web services fulfilling criteria for the user query. To fulfil the end-user query, conventional web services matching is done through keyword-based algorithms. Unlike conventional web services, semantic web services require to measure the semantic similarity of web service descriptions. This is usually done based on Input, Output, Pre-condition & Effect (IOPE) parameters associated with web services. A past experimental study reveals that the web service selection process is driven through semantics measures and performs better than various other keyword-based approaches [1–3]. Furthermore, the algorithms, such as fuzzy neural network, ant colony optimization, whale optimization algorithm, implemented for software rejuvenation also affect the web service selection process and its performance based on different parameters [4–7].
Present and future of semantic web technologies: a research statement
Published in International Journal of Computers and Applications, 2021
For the development of the IoT, many semantic technologies such as ontologies, semantic annotation, RDF, linked data, semantic web service, and so on can be used as a principal solution. The use of ontology with a semantic description for data will make it interoperable for clients who share and utilize the same ontology. Through semantic technologies in IoT, we can handle interoperability, efficient data processing, resource discovery, integration, reasoning, and querying. Likewise, semantic technologies have demonstrated their usefulness in different areas, and a few among various problems that SWTs are addressing are to (i) reduce heterogeneity by using semantic interoperability, (ii) provide simple integration of data application, (iii) infer and mine new knowledge to develop applications and provide smart solutions, and (iv) provide interoperability between different data processes with representation, management, and storage of data.
A context-based service matching approach towards functional reliability for industrial systems
Published in Enterprise Information Systems, 2019
Chengxi Huang, Li Da Xu, Hongming Cai, Guoqiang Li, Jiawei Du, Lihong Jiang
As to service discovery in complex environment,(Han, Lee, and Crespi 2014) presents a building automation system adopting SOA paradigm with devices implemented by device profile for web service. (Dong and Hussain 2014) presents a self-adaptive semantic fo- cused crawler for precisely and efficiently discovering, formatting, and indexing mining service information. (Baresi, Miraz, and Plebani 2016) introduces a distributed architecture DREAM that supports different ways to evaluate the matching between published and required services. (Ahmed et al. 2015) propose a context-aware service discovery and selection approach in a decentralized peer-to-peer environment. And (Mier et al. 2015) pro- vides a integrated semantic Web service discovery and composition framework. Bansal et al. (2016) presents a framework that filters and ranks solutions based on their trust ratings.