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Ontology for Mobile Phone Operating Systems

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This ongoing study deals with an important part of a line of research that constitutes a challenging burden. It is an initial investigation into the development of a Holistic Framework for Cellular Communication (HFCC). The main purpose is to establish mechanisms by which existing wireless cellular communication components and models can work holistically together. It demonstrates that establishing a mathematical framework that allows existing cellular communication technologies (and tools supporting those technologies) to seamlessly interact is technically feasible. The longer-term future goals are to actually improve the interoperability, the efficiency of mobile communication, calls quality, and reliability by applying the framework to specific development efforts.
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... Our proposal adds diverse data, sensors, and details the description of various platform types. In addition, HSSN does not contain domain specific knowledge and can be easily aligned with other ontology models (e.g., a mobile phone [47], smart building ontology [94]). ...
Thesis
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The rising interest in smart connected environments (e.g., smart buildings, cities, factories) and theevolution of sensors, data management/communication technologies have paved the way forinteresting and useful applications that help users in their every day tasks (e.g. increasing comfort,reducing energy consumption). However, various improvements are still required. For instance, howto enhance the representation of such complex, dynamic, and heterogeneous environments.Moreover, how to facilitate the interaction between users and their connected environments, and howto provide tools for environment monitoring and management.In this thesis, we focus on four main challenges: (i) representing a diverse set of components andelements related to the environment and its sensor network; (ii) providing a query language thathandles user/connected environment interactions (e.g., environment definition, data management,event definition); (iii) coping with the dynamicity of the environment and its evolution over time; and(iv) proposing a generic event detection mechanism for improved environment monitoring.To do so, we first present an ontology-based data model that represents hybrid environments/sensornetworks. Thus covering diverse sensors (e.g., static, mobile), environments (e.g., infrastructures,devices), and data (e.g., scalar, multimedia). Then, we introduce a query language that one might usefor various tasks (e.g., defining the connected environment, information retrieval, event definition,data management). Furthermore, to keep up with the environment changes we provide a queryoptimizer that allows the submitted queries to cope with the dynamicity of the environment prior totheir execution. Finally, we propose an event detection core that takes event definitions as input anddetects the targeted events.We group the aforementioned modules in one global framework for event detection in connectedenvironments. Our proposal is generic, extensible, and could be used with different connectedenvironments such as buildings, cities. . .
... In this regard, we focused specifically on a detailed analysis of the characteristics of consumer reviews. Additionally, we consulted specific dictionaries, a thesaurus, and some research where mobile ontologies were built [73,74], comparing entities and adding some words that were not found automatically. Finally, we manually identified the relationships between the discovered features. ...
Article
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Companies have realized the importance of “big data” in creating a sustainable competitive advantage, and user-generated content (UGC) represents one of big data’s most important sources. From blogs to social media and online reviews, consumers generate a huge amount of brand-related information that has a decisive potential business value for marketing purposes. Particularly, we focus on online reviews that could have an influence on brand image and positioning. Within this context, and using the usual quantitative star score ratings, a recent stream of research has employed sentiment analysis (SA) tools to examine the textual content of reviews and categorize buyer opinions. Although many SA tools split comments into negative or positive, a review can contain phrases with different polarities because the user can have different sentiments about each feature of the product. Finding the polarity of each feature can be interesting for product managers and brand management. In this paper, we present a general framework that uses natural language processing (NLP) techniques, including sentiment analysis, text data mining, and clustering techniques, to obtain new scores based on consumer sentiments for different product features. The main contribution of our proposal is the combination of price and the aforementioned scores to define a new global score for the product, which allows us to obtain a ranking according to product features. Furthermore, the products can be classified according to their positive, neutral, or negative features (visualized on dashboards), helping consumers with their sustainable purchasing behavior. We proved the validity of our approach in a case study using big data extracted from Amazon online reviews (specifically cell phones), obtaining satisfactory and promising results. After the experimentation, we could conclude that our work is able to improve recommender systems by using positive, neutral, and negative customer opinions and by classifying customers based on their comments.
... There is an OntoGraf feature that provides interactive support for navigating the OWL ontology relationship. Various layouts are supported to regulate the structure of the ontology [15]. The types of data relationships supported include subclass, individual, domain or range object properties, and equivalence. ...
... This device description ontology is then used for formal design and commissioning of modern building automation systems. Another example is the mobile operating system ontology [17] has been developed by Hasni et al. by federating two single ontologies of Symbian and android operating systems. ...
Preprint
Today's ubiquitous computing ecosystem involves various kinds of hardware and software technologies for different computing environments. As the result, computing systems can be seen as integrated system of hardware and software systems. Realizing such complex systems is crucial for providing safety, security, and maintenance. This is while the characterization of computing systems is not possible without a systematic procedure for enumerating different components and their structural/behavioral relationships. Architecture Reconstruction (AR) is a practice defined in the domain of software engineering for the realization of a specific software component. However, it is not applicable to a whole system (including HW/SW). Inspired by Symphony AR framework, we have proposed a generalized method to reconstruct the architecture of a computing platform at HW/SW boundary. In order to cover diverge set of existing HW/SW technologies, our method uses an ontology-based approach to handle these complexities. Due to the lack of a comprehensive accurate ontology in the literature, we have developed our own ontology -- called PLATOnt -- which is shown to be more effective by ONTOQA evaluation framework. We have used our AR method in two use case scenarios to reconstruct the architecture of ARM-based Trusted execution environment and a Raspberry-pi platform have extensive application in embedded systems and IoT devices.
... In these studies, common features and variations are automatically extracted from source code [4], [5], [6] or product descriptions [7]. ...
Article
To address the vast variety of computing requirements in recent ubiquitous computing ecosystem, there is a constant need for more complex computing systems that consist of integrated hardware (HW) and software (SW) systems. Providing an architectural insight into such systems helps in achieving a more efficient usage of system resources, verifying the characteristics of a platform and provisioning of its security and trust. Architecture reconstruction (AR) has been used in software engineering to gain a deeper insight into specific software. Neither software AR nor hardware reverse engineering techniques are sufficient to extract the architecture of a system that incorporates both HW/SW, since they are unable to recover the relationships between the HW and SW components. Inspired by the Symphony software AR framework, we propose a method to reconstruct the architecture of a computing platform as a whole. In order to cover the wide variety of existing HW/SW technologies, our method uses an ontology-based approach. Due to the lack of a comprehensive ontology in literature, we developed PLATOnt, a new ontology that has been shown to be more effective by OntoQA evaluation framework. We used our AR method to reconstruct the architecture of an ARM-based trusted execution environment and a Raspberry Pi platform, widely used in embedded systems and IoT devices.
Thesis
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The automation of software development has long been a goal of software engineering to increase efficiency of the development effort and improve the software product. This efficiency (high productivity with less software faults) results from best practices in building, managing and tes ting software projects via the use of these automated tools and processes. However, each software development tool has its own characteristics, semantics, objects, and concepts. While there have been significant results achieved by use of automated software development tools (coming mainly from the widespread increase of customers’ adoption of these tools), there remains many challenging obstacles: lack of communication between the different software development tools, poor shared understanding; use of di fferent syntax and concepts between tools, limits in interoperability between tools, absence of a unifying conceptual models and ideas between tools, and redundant work and cross purposes between tools. The approach undertaken in this thesis to overcome th ese obstacles was to construct a “pilot” ontology that is extensible. We applied the Feature-Oriented Domain Analysis approach to capture the commonalities between two software development tools (Rational Software Corporation's RequisitePro, a main -stream, complex, commercial tool), and a software prototyping tool (the Software Engineering Automation tool (SEATools), a research model with tool support for developing executable software prototypes) and developed an ontology for the software development tools using the Protégé -2000 System. The ontology expressed in UML, promotes interoperability and enhanced communication.
Article
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Recent work in Artificial Intelligence (AI) is exploring the use of formal ontologies as a way of specifying content-specific agreements for the sharing and reuse of knowledge among software entities. We take an engineering perspective on the development of such ontologies. Formal ontologies are viewed as designed artifacts, formulated for specific purposes and evaluated against objective design criteria. We describe the role of ontologies in supporting knowledge sharing activities, and then present a set of criteria to guide the development of ontologies for these purposes. We show how these criteria are applied in case studies from the design of ontologies for engineering mathematics and bibliographic data. Selected design decisions are discussed, and alternative representation choices are evaluated against the design criteria.
Article
In the context of software product-lines the configuration knowledge describing how requirements are mapped onto elements of the reuse framework is essential for the suc- cess of the product-line. The starting point of this mapping process can be a feature model which describes the func- tionality to be found in the domain on an abstract level. In this paper we present an approach for the description of feature models which offers a tool-supported selection of features and a connection of this information to the further steps of application development. 1I ntroduction The highly competitive and dynamic field of software development implies the need to continuously increase the efficiency of development processes. Software reuse and especially the principle of product-lines are commonly recognized approaches to address this problem. The prod- uct-line process can thereby be seen as a two-staged pro- cess. In the first stage during domain engineering the product-line is initialized by the definition of the scope of the domain, i.e. by defining the real world aspects which are part of the product-line. In a later step a reuse frame- work is built which comprises requirements models, and a reference architecture as the basic structure for all systems in the product-line, as well as components which are reused during the implementation of applications in the domain. The second stage contains the actual application engi- neering process which is performed for every application of the product-line. In this process the reuse framework built during domain engineering is used as a skeleton that is extended to the needs of a specific application. E.g., the requirements models developed during the domain analy- sis are extended by specific requirements in order to com- plete the specification. This specification is later used to instantiate the given reference architecture. An important part of the requirements models is a description of the feature model. The feature model is an abstract representation of functionality found in the domain. Each feature thereby is a relevant characteristic of the domain. The feature model is used during domain engineering in order to obtain an abstract view on this functionality which can be verified against the needs raised by the domain. The primary purpose of feature modeling, however, is the configuration of the product- line during the application engineering process. Since the reusable infrastructure already exists, it is possible to describe which parts of the reference architecture imple- ment a single feature. With this knowledge in mind it is possible to trace decisions on the level of the feature model down to relevant components of the architecture. In contrast, it is also possible to exclude parts of the architec- ture based on the decision not to include certain features. This paper describes an approach for the formalization of feature models which is based on the design space tech- nique. This technique is well suited for the tool supported selection of features as well as the deployment of the fea- ture selection in further steps of the development process. The paper is structured as follows. The next section gives a short overview of feature modeling as it is currently seen in the research community. Section 3 contains a descrip- tion of the design space technique whose deployment for feature modeling in the context of our software develop- ment process is explained in section 4. In section 5, short usage scenarios are given which describe the further appli- cation of the feature selection during the configuration of the product-line. Finally, section 6 gives some concluding remarks and an outlook on further work.
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This paper is intended to serve as a comprehensive introduction to the emerging field concerned with the design and use of ontologies. We observe that disparate backgrounds, languages, tools, and techniques are a major barrier to effective communication among people, organisations, and/or software systems. We show how the development and implementation of an explicit account of a shared understanding (i.e. an `ontology') in a given subject area, can improve such communication, which in turn, can give rise to greater reuse and sharing, inter-operability, and more reliable software. After motivating their need, we clarify just what ontologies are and what purposes they serve. We outline a methodology for developing and evaluating ontologies, first discussing informal techniques, concerning such issues as scoping, handling ambiguity, reaching agreement and producing definitions. We then consider the benefits of and describe, a more formal approach. We re-visit the scoping phase, and discuss the role of formal languages and techniques in the specification, implementation and evaluation of ontologies. Finally, we review the state of the art and practice in this emerging field, considering various case studies, software tools for ontology development, key reearch issues and future prospects.
Analysis of the Android Architecture Karlsruhe institute for technology Toward Principles for the Design of Ontologies Used for Knowledge Sharing
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