256 research outputs found
PicAlert!: a system for privacy-aware image classification and retrieval
No full textPhoto publishing in Social Networks and other Web2.0 applications has become very popular due to the pervasive availability of cheap digital cameras, powerful batch upload tools and a huge amount of storage space. A portion of uploaded images are of a highly sensitive nature, disclosing many details of the users’ private life. We have developed a web service which can detect private images within a user’s photo stream and provide support in making privacy decisions in the sharing context. In addition, we present a privacy-oriented image search application which automatically identifies potentially sensitive images in the result set and separates them from the remaining picture
Die Erschließung von Primärmaterial qualitativer Studien für die Sekundäranalyse als Herausforderung für Sozialwissenschaften und Informatik
No full textIm vergangenen Jahrzehnt ist das Interesse an der wissenschaftlichen Nachnutzung des Materials aus früheren qualitativen sozialwissenschaftlichen Studien gestiegen. Im Kontrast dazu steht das bisher bescheidene Volumen an für sekundäranalytische Forschung archivierten und genutzten Datensätzen. Dieses Papier gibt einen Überblick über die dahinterstehenden Daten- und Archivierungsprobleme und die Möglichkeiten, über eine Kombination aus manuellen und IT-Werkzeugen eine wesentliche Hürde des Forschungsprozesses - die Auswahl geeigneten Forschungsmaterials - zu überwinden
Dataset "Privacy-aware image classification and search"
No full textModern content sharing environments such as Flickr or YouTube contain a large number of private resources such as photos showing weddings, family holidays, and private parties. These resources can be of a highly sensitive nature, disclosing many details of the users' private sphere. In order to support users in making privacy decisions in the context of image sharing and to provide them with a better overview of privacy-related visual content available on the Web, we propose techniques to automatically detect private images and to enable privacy-oriented image search. In order to classify images, we use the metadata like title and tags and plan to use visual features which are described in our scientific paper. The data set used in the paper is now available. Picalet! cleaned dataset - ( recommended for experiments) userstudy - (images annotated with queries, anonymized user id and privacy value)</span
Using microtasks to crowdsource DBpedia entity classification: A study in workflow design
No full textDBpedia is at the core of the Linked Open Data Cloud and widely used in research and applications. However, it is far from being perfect. Its content suffers from many flaws, as a result of factual errors inherited from Wikipedia or incomplete mappings from Wikipedia infobox to DBpedia ontology. In this work we focus on one class of such problems, un-typed entities. We propose a hierarchical tree-based approach to categorize DBpedia entities according to the DBpedia ontology using human computation and paid microtasks. We analyse the main dimensions of the crowdsourcing exercise in depth in order to come up with suggestions for workflow design and study three different workflows with automatic and hybrid prediction mechanisms to select possible candidates for the most specific category from the DBpedia ontology. To test our approach, we run experiments on CrowdFlower using a gold standard dataset of 120 previously unclassified entities. In our studies human-computation driven approaches generally achieved higher precision at lower cost when compared to workflows with automatic predictors. However, each of the tested workflows has its merit and none of them seems to perform exceptionally well on the entities that the DBpedia Extraction Framework fails to classify. We discuss these findings and their potential implications for the design of effective crowdsourced entity classification in DBpedia and beyond
From crowd to community: a survey of online community features in citizen science projects
No full textOnline citizen science projects have been increasingly used in a variety of disciplines and contexts to enable large-scale scientific research. The successes of such projects have encouraged the development of customisable platforms to enable anyone to run their own citizen science project. However, the process of designing and building a citizen science project remains complex, with projects requiring both human computation and social aspects to sustain user motivation and achieve project goals. In this paper, we conduct a systematic survey of 48 citizen science projects to identify common features and functionality. Supported by online community literature, we use structured walkthroughs to identify different mechanisms used to encourage volunteer contributions across four dimensions: task visibility, goals, feedback, and rewards. Our findings contribute to the ongoing discussion on citizen science design and the relationship between community and microtask design for achieving successful outcomes
Respiratory Circuits: Function, Mechanisms, Topology, and Pathology
No full textNeuroscientists have long sought to understand how circuits in the nervous system are organized to generate the precise neural outputs that underlie particular behaviors. Recent studies deepened our understanding of the mechanisms responsible for the generation of the rhythmic output for breathing. Here, the author focuses on issues that are pertinent for the respiratory network and considers its organization and how it derives the functional output. The author discusses pacemaker and network mechanisms of rhythm generation, which are now combined into a novel concept of emergent network activity due to coherent excitation of pacemaker groups. He discusses subcellular basis of this hypothesis and possible mechanisms of synchronization within respiratory network. These new findings in respiratory neuroscience are further applied to explain modifications in breathing during hypoxia and possible origins of respiratory disorders that may be acquired during neural development and aging
Providing Social Sharing Functionalities in LearnWeb2.0
No full textMarenzi, I., Zerr, S., & Nejdl, W. (2008). Providing Social Sharing Functionalities in LearnWeb2.0. In R. Koper, K. Stefanov & D. Dicheva (Eds). Proceedings of the 5th International TENCompetence Open Workshop "Stimulating Personal Development and Knowledge Sharing" (pp. 9-14). October, 30-31, 2008, Sofia, Bulgaria: TENCompetence Workshop. [For the whole proceedings please see also http://hdl.handle.net/1820/1961 ]Within the TENCompetence project we are
working on an open source infrastructure for the
creation, storage and exchange of learning
objects and knowledge resources. We
implemented LearnWeb2.0 - a prototype, which
provides appropriate functionalities for the
aggregation and annotation of Web 2.0
resources for lifelong competence development
activities. This paper focuses on the next steps
planned, describing the main functionalities to
be implemented in LearnWeb2.0: resource
selection, batch annotation and sharing,
notification using SpreadCrumbs, resource
aggregation using GroupMe and sequencing,
motivated by a knowledge sharing scenario at
the University of Pavia.The work on this publication has been sponsored by the TENCompetence Integrated Project that is funded by the European Commission's 6th Framework Programme, priority IST/Technology Enhanced Learning. Contract 027087 [http://www.tencompetence.org
Zerber+R: Top-k Retrieval from a Confidential Index
No full textZerr, S., Olmedilla, D., Nejdl, W., & Siberski, W. (2009). Zerber+R: Top-k Retrieval from a Confidential Index. Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology (pp. 439-449). March, 24-26, 2009, Saint Petersburg, Russia (ISBN: 978-1-60558-422-5).Privacy-preserving document exchange among collaboration groups in an enterprise as well as across enterprises requires techniques for sharing and search of access-controlled information through largely untrusted servers. In these settings search systems need to provide confidentiality guarantees for shared information while offering IR properties comparable to the ordinary search engines. Top-k is a standard IR technique which enables fast query execution on very large indexes and makes systems highly scalable. However, indexing access-controlled information for top-k retrieval is a challenging task due to the sensitivity of the term statistics used for ranking.
In this paper we present Zerber+R -- a ranking model which allows for privacy-preserving top-k retrieval from an outsourced inverted index. We propose a relevance score transformation function which makes relevance scores of different terms indistinguishable, such that even if stored on an untrusted server they do not reveal information about the indexed data. Experiments on two real-world data sets show that Zerber+R makes economical usage of bandwidth and offers retrieval properties comparable with an ordinary inverted index.The work on this publication has been sponsored by the TENCompetence Integrated Project that is funded by the European Commission's 6th Framework Programme, priority IST/Technology Enhanced Learning. Contract 027087 [http://www.tencompetence.org
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