The FORA Framework - A Fuzzy Grassroots Ontology for Online Reputation Management

Online reputation management deals with monitoring and influencing the online record of a person, an organization or a product. The Social Web offers increasingly simple ways to publish and disseminate personal or opinionated information, which can rapidly have a disastrous influence on the online reputation of some of the entities. The author focuses on the Social Web and possibilities of its integration with the Semantic Web as resource for a semi-automated tracking of online reputations using imprecise natural language terms. The inherent structure of natural language supports humans not only in communication but also in the perception of the world. Thereby fuzziness is a promising tool for transforming those human perceptions into computer artifacts. Through fuzzy grassroots ontologies, the Social Semantic Web becomes more naturally and thus can streamline online reputation management. For readers interested in the cross-over field of computer science, information systems, and social sciences, this book is an ideal source for becoming acquainted with the evolving field of fuzzy online reputation management in the Social Semantic Web area. ​

Customized mashups for improved reputation visualization

This document describes a possible use for the YouReputation API. A mashup combining the YouReputation and the Flickr APIs attempts to improve the visualization of reputation. First, this paper gives an introduction to Web services and APIs and further explains the developed prototype. This paper introduces an API that can be easily combined with other APIs to improve the representation of reputation terms and therefore enhance usability and design.

The FORA Framework - A Fuzzy Grassroots Ontology for Online Reputation Management

Online reputation management deals with monitoring and influencing the online record of a person, an organization or a product. The Social Web offers increasingly simple ways to publish and disseminate personal or opinionated information, which can rapidly have a disastrous influence on the online reputation of some of the entities. This dissertation can be split into three parts: In the first part, possible fuzzy clustering applications for the Social Semantic Web are investigated. The second part explores promising Social Semantic Web elements for organizational applications,while in the third part the former two parts are brought together and a fuzzy online reputation analysis framework is introduced and evaluated. Theentire PhD thesis is based on literature reviews as well as on argumentative-deductive analyses.The possible applications of Social Semantic Web elements within organizations have been researched using a scenario and an additional case study together with two ancillary case studies—based on qualitative interviews. For the conception and implementation of the online reputation analysis application, a conceptual framework was developed. Employing test installations and prototyping, the essential parts of the framework have been implemented.By following a design sciences research approach, this PhD has created two artifacts: a frameworkand a prototype as proof of concept. Bothartifactshinge on twocoreelements: a (cluster analysis-based) translation of tags used in the Social Web to a computer-understandable fuzzy grassroots ontology for the Semantic Web, and a (Topic Maps-based) knowledge representation system, which facilitates a natural interaction with the fuzzy grassroots ontology. This is beneficial to the identification of unknown but essential Web data that could not be realized through conventional online reputation analysis. Theinherent structure of natural language supports humans not only in communication but also in the perception of the world. Fuzziness is a promising tool for transforming those human perceptions intocomputer artifacts. Through fuzzy grassroots ontologies, the Social Semantic Web becomes more naturally and thus can streamline online reputation management.

A Fuzzy Grassroots Ontology for improving Weblog Extraction

This paper presents fuzzy clustering algorithms to establish a grassroots ontology – a machine-generated weak ontology – based on folksonomies. Furthermore, it describes a search engine for vaguely associated terms and aggregates them into several meaningful cluster categories, based on the introduced weak grassroots ontology. A potential application of this ontology, weblog extraction, is illustrated using a simple example. Added value and possible future studies are discussed in the conclusion.

The ovine cerebral venous system: comparative anatomy, visualization, and implications for translational research.

Cerebrovascular diseases are significant causes of death and disability in humans. Improvements in diagnostic and therapeutic approaches strongly rely on adequate gyrencephalic, large animal models being demanded for translational research. Ovine stroke models may represent a promising approach but are currently limited by insufficient knowledge regarding the venous system of the cerebral angioarchitecture. The present study was intended to provide a comprehensive anatomical analysis of the intracranial venous system in sheep as a reliable basis for the interpretation of experimental results in such ovine models. We used corrosion casts as well as contrast-enhanced magnetic resonance venography to scrutinize blood drainage from the brain. This combined approach yielded detailed and, to some extent, novel findings. In particular, we provide evidence for chordae Willisii and lateral venous lacunae, and report on connections between the dorsal and ventral sinuses in this species. For the first time, we also describe venous confluences in the deep cerebral venous system and an 'anterior condylar confluent' as seen in humans. This report provides a detailed reference for the interpretation of venous diagnostic imaging findings in sheep, including an assessment of structure detectability by in vivo (imaging) versus ex vivo (corrosion cast) visualization methods. Moreover, it features a comprehensive interspecies-comparison of the venous cerebral angioarchitecture in man, rodents, canines and sheep as a relevant large animal model species, and describes possible implications for translational cerebrovascular research.

Universal ontology: attentive tracking of objects and substances across languages and over development

Previous research has demonstrated that adults are successful at visually tracking rigidly moving items, but experience great difficulties when tracking substance-like ‘‘pouring’’ items. Using a comparative approach, we investigated whether the presence/absence of the grammatical count–mass distinction influences adults and children’s ability to attentively track objects versus substances. More specifically, we aimed to explore whether the higher success at tracking rigid over substance-like items appears universally or whether speakers of classifier languages (like Japanese, not marking the object–substance distinction) are advantaged at tracking substances as compared to speakers of non-classifier languages (like Swiss German, marking the object–substance distinction). Our results supported the idea that language has no effect on low-level cognitive processes such as the attentive visual processing of objects and substances. We concluded arguing that the tendency to prioritize objects is universal and independent of specific characteristics of the language spoken.