Usage-driven Maintenance of Knowledge Organization Systems

Knowledge Organization Systems (KOS) are typically used as background knowledge for document indexing in information retrieval. They have to be maintained and adapted constantly to reflect changes in the domain and the terminology. In this thesis, approaches are provided that support the maintenance of hierarchical knowledge organization systems, like thesauri, classifications, or taxonomies, by making information about the usage of KOS concepts available to the maintainer. The central contribution is the ICE-Map Visualization, a treemap-based visualization on top of a generalized statistical framework that is able to visualize almost arbitrary usage information. The proper selection of an existing KOS for available documents and the evaluation of a KOS for different indexing techniques by means of the ICE-Map Visualization is demonstrated. For the creation of a new KOS, an approach based on crowdsourcing is presented that uses feedback from Amazon Mechanical Turk to relate terms hierarchically. The extension of an existing KOS with new terms derived from the documents to be indexed is performed with a machine-learning approach that relates the terms to existing concepts in the hierarchy. The features are derived from text snippets in the result list of a web search engine. For the splitting of overpopulated concepts into new subconcepts, an interactive clustering approach is presented that is able to propose names for the new subconcepts. The implementation of a framework is described that integrates all approaches of this thesis and contains the reference implementation of the ICE-Map Visualization. It is extendable and supports the implementation of evaluation methods that build on other evaluations. Additionally, it supports the visualization of the results and the implementation of new visualizations. An important building block for practical applications is the simple linguistic indexer that is presented as minor contribution. It is knowledge-poor and works without any training. This thesis applies computer science approaches in the domain of information science. The introduction describes the foundations in information science; in the conclusion, the focus is set on the relevance for practical applications, especially regarding the handling of different qualities of KOSs due to automatic and semiautomatic maintenance

Advanced Location-Based Technologies and Services

Since the publication of the first edition in 2004, advances in mobile devices, positioning sensors, WiFi fingerprinting, and wireless communications, among others, have paved the way for developing new and advanced location-based services (LBSs). This second edition provides up-to-date information on LBSs, including WiFi fingerprinting, mobile computing, geospatial clouds, geospatial data mining, location privacy, and location-based social networking. It also includes new chapters on application areas such as LBSs for public health, indoor navigation, and advertising. In addition, the chapter on remote sensing has been revised to address advancements

Dimensional Modeling of Emotions in Text with Appraisal Theories: Corpus Creation, Annotation Reliability, and Prediction

The most prominent tasks in emotion analysis are to assign emotions to texts and to understand how emotions manifest in language. An observation for NLP is that emotions can be communicated implicitly by referring to events, appealing to an empathetic, intersubjective understanding of events, even without explicitly mentioning an emotion name. In psychology, the class of emotion theories known as appraisal theories aims at explaining the link between events and emotions. Appraisals can be formalized as variables that measure a cognitive evaluation by people living through an event that they consider relevant. They include the assessment if an event is novel, if the person considers themselves to be responsible, if it is in line with the own goals, and many others. Such appraisals explain which emotions are developed based on an event, e.g., that a novel situation can induce surprise or one with uncertain consequences could evoke fear. We analyze the suitability of appraisal theories for emotion analysis in text with the goal of understanding if appraisal concepts can reliably be reconstructed by annotators, if they can be predicted by text classifiers, and if appraisal concepts help to identify emotion categories. To achieve that, we compile a corpus by asking people to textually describe events that triggered particular emotions and to disclose their appraisals. Then, we ask readers to reconstruct emotions and appraisals from the text. This setup allows us to measure if emotions and appraisals can be recovered purely from text and provides a human baseline. Our comparison of text classification methods to human annotators shows that both can reliably detect emotions and appraisals with similar performance. Therefore, appraisals constitute an alternative computational emotion analysis paradigm and further improve the categorization of emotions in text with joint models.Comment: Computational Linguistics Journal in Issue No 1, March 2023; 71 pages, 13 figures, 19 table

Security and Privacy in Mobile Computing: Challenges and Solutions

abstract: Mobile devices are penetrating everyday life. According to a recent Cisco report [10], the number of mobile connected devices such as smartphones, tablets, laptops, eReaders, and Machine-to-Machine (M2M) modules will hit 11.6 billion by 2021, exceeding the world's projected population at that time (7.8 billion). The rapid development of mobile devices has brought a number of emerging security and privacy issues in mobile computing. This dissertation aims to address a number of challenging security and privacy issues in mobile computing. This dissertation makes fivefold contributions. The first and second parts study the security and privacy issues in Device-to-Device communications. Specifically, the first part develops a novel scheme to enable a new way of trust relationship called spatiotemporal matching in a privacy-preserving and efficient fashion. To enhance the secure communication among mobile users, the second part proposes a game-theoretical framework to stimulate the cooperative shared secret key generation among mobile users. The third and fourth parts investigate the security and privacy issues in mobile crowdsourcing. In particular, the third part presents a secure and privacy-preserving mobile crowdsourcing system which strikes a good balance among object security, user privacy, and system efficiency. The fourth part demonstrates a differentially private distributed stream monitoring system via mobile crowdsourcing. Finally, the fifth part proposes VISIBLE, a novel video-assisted keystroke inference framework that allows an attacker to infer a tablet user's typed inputs on the touchscreen by recording and analyzing the video of the tablet backside during the user's input process. Besides, some potential countermeasures to this attack are also discussed. This dissertation sheds the light on the state-of-the-art security and privacy issues in mobile computing.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Proceedings of the 2nd Conference on Production Systems and Logistics (CPSL 2021)

Proceedings of the CPSL 202

Credibility in Online Social Networks: A Survey

The importance of information credibility in society cannot be underestimated given that it is at the heart of all decision-making. Generally, more information is better; however, knowing the value of this information is essential for the decision-making processes. Information credibility defines a measure of the fitness of the information for consumption. It can also be defined in terms of reliability, which denotes the probability that a data source will appear credible to the users. A challenge in this topic is that there is a great deal of literature that has developed different credibility dimensions. In addition, information science dealing with online social networks has grown in complexity, attracting interest from researchers in information science, psychology, human–computer interaction, communication studies, and management studies, all of whom have studied the topic from different perspectives. This work will attempt to provide an overall review of the credibility assessment literature over the period 2006–2017 as applied to the context of the microblogging platform, Twitter. The known interpretations of credibility will be examined, particularly as they relate to the Twitter environment. In addition, we investigate levels of credibility assessment features. We then discuss recent works, addressing a new taxonomy of credibility analysis and assessment techniques. At last, a cross-referencing of literature is performed while suggesting new topics for future studies of credibility assessment in a social media context

Mobile Collaborative Learning for Female Baby Boomer Students in Canadian Higher Education

Female baby boomer students (born 1946-1964) need to augment their skills in mobile collaborative learning because current knowledge of technologies is essential for making informed decisions. The purpose of this study was to determine the need to promote technologies based on the experiences of female baby boomer students. Andragogy and constructivism provided the conceptual framework for this research. The research questions were devised to investigate female boomer students\u27 collaborative experiences using smart devices and barriers to their adoption of technology. This phenomenological study included 8 participants from a Canadian university recruited through purposeful sampling. Per the Modified Stevick-Colaizzi-Keen method, data were simultaneously collected via interviews, analyzed by coding, and organized into themes until saturation. Age was the main deterrent for technology adoption, and obstacles included embracing a new process, feeling that information was secure, and resolving technical difficulties. Results indicated that female baby boomer students were not ready to lead in the use of mobile collaborative learning and could not maintain rapid technological changes. Mature students may need training in cloud computing; a 1-semester blended course was proposed to enable these students to learn mobile technologies and collaborative skills. This study identifies the technology learning needs of baby boomer students, which will help those looking for ways to teach students in this age range. When leaders in their field of study know how to use current technologies, they will be more productive in their communities

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse