004 Datenverarbeitung; Informatik
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The continuously increasing number of biomedical scholarly publications makes it challenging to construct document recommendation algorithms that can efficiently navigate through literature. Such algorithms would help researchers in finding similar, relevant, and related publications that align with their research interests. Natural Language Processing offers various alternatives to compare publications, ranging from entity recognition to document embeddings. In this paper, we present the results of a comparative analysis of vector-based approaches to assess document similarity in the RELISH corpus. We aim to determine the best approach that resembles relevance without the need for further training. Specifically, we employ five different techniques to generate vectors representing the text in the documents. These techniques employ a combination of various Natural Language Processing frameworks such as Word2Vec, Doc2Vec, dictionary-based Named Entity Recognition, and state-of-the-art models based on BERT. To evaluate the document similarity obtained by these approaches, we utilize different evaluation metrics that account for relevance judgment, relevance search, and re-ranking of the relevance search. Our results demonstrate that the most promising approach is an in-house version of document embeddings, starting with word embeddings and using centroids to aggregate them by document.
Smart heating systems are one of the core components of smart homes. A large portion of domestic energy consumption is derived from HVAC (heating, ventilation and air conditioning) systems, making them a relevant topic of the efforts to support an energy transition in private housing. For that reason, the technology has attracted attention both from the academic and the industry communities. User interfaces of smart heating systems have evolved from simple adjusting knobs to advanced data visualization interfaces, that allow for more advanced setting such as time tables and status information. With the advent of AI, we are interested in exploring how the interfaces will be evolving to build the connection between user needs and underlying AI system. Hence, this paper is targeted to provide early design implications towards an AI-based user interface for smart heating systems.
AI systems pose unknown challenges for designers, policymakers, and users which aggravates the assessment of potential harms and outcomes. Although understanding risks is a requirement for building trust in technology, users are often excluded from legal assessments and explanations of AI hazards. To address this issue we conducted three focus groups with 18 participants in total and discussed the European proposal for a legal framework for AI. Based on this, we aim to build a (conceptual) model that guides policymakers, designers, and researchers in understanding users’ risk perception of AI systems. In this paper, we provide selected examples based on our preliminary results. Moreover, we argue for the benefits of such a perspective.
When dialogues with voice assistants (VAs) fall apart, users often become confused or even frustrated. To address these issues and related privacy concerns, Amazon recently introduced a feature allowing Alexa users to inquire about why it behaved in a certain way. But how do users perceive this new feature? In this paper, we present preliminary results from research conducted as part of a three-year project involving 33 German households. This project utilized interviews, fieldwork, and co-design workshops to identify common unexpected behaviors of VAs, as well as users’ needs and expectations for explanations. Our findings show that, contrary to its intended purpose, the new feature actually exacerbates user confusion and frustration instead of clarifying Alexa's behavior. We argue that such voice interactions should be characterized as explanatory dialogs that account for VA’s unexpected behavior by providing interpretable information and prompting users to take action to improve their current and future interactions.
Ziel der neunten Ausgabe des wissenschaftlichen Workshops "Usable Security und Privacy" auf der Mensch und Computer 2023 ist es, aktuelle Forschungs- und Praxisbeiträge auf diesem Gebiet zu präsentieren und mit den Teilnehmer:innen zu diskutieren. Getreu dem Konferenzmotto "Building Bridges" soll mit dem Workshop ein etabliertes Forum fortgeführt und weiterentwickelt werden, in dem sich Expert:innen, Forscher:innen und Praktiker:innen aus unterschiedlichen Domänen transdisziplinär zum Thema Usable Security und Privacy austauschen können. Das Thema betrifft neben dem Usability- und Security-Engineering unterschiedliche Forschungsgebiete und Berufsfelder, z. B. Informatik, Ingenieurwissenschaften, Mediengestaltung und Psychologie. Der Workshop richtet sich an interessierte Wissenschaftler:innen aus all diesen Bereichen, aber auch ausdrücklich an Vertreter:innen der Wirtschaft, Industrie und öffentlichen Verwaltung.
The representation, or encoding, utilized in evolutionary algorithms has a substantial effect on their performance. Examination of the suitability of widely used representations for quality diversity optimization (QD) in robotic domains has yielded inconsistent results regarding the most appropriate encoding method. Given the domain-dependent nature of QD, additional evidence from other domains is necessary. This study compares the impact of several representations, including direct encoding, a dictionary-based representation, parametric encoding, compositional pattern producing networks, and cellular automata, on the generation of voxelized meshes in an architecture setting. The results reveal that some indirect encodings outperform direct encodings and can generate more diverse solution sets, especially when considering full phenotypic diversity. The paper introduces a multi-encoding QD approach that incorporates all evaluated representations in the same archive. Species of encodings compete on the basis of phenotypic features, leading to an approach that demonstrates similar performance to the best single-encoding QD approach. This is noteworthy, as it does not always require the contribution of the best-performing single encoding.
LiDAR-based Indoor Localization with Optimal Particle Filters using Surface Normal Constraints
(2023)
The continuous increase of biomedical scholarly publications makes it challenging to construct document recommendation algorithms to navigate through literature, an important feature for researchers to keep up with relevant publications. Understanding semantic relatedness and similarity between two documents could improve document recommendations. The objective of this study is performing a comparative analysis of vector-based approaches to assess document similarity in the RELISH corpus. Here we present our approach to compare five different techniques to generate vectors representing the text in the documents. These techniques employ a combination of various Natural Language Processing frameworks such as Word2Vec, Doc2Vec, dictionary-based Named Entity Recognition as well as state-of-the-art models based on BERT.
Here we present a doc-2-doc relevance assessment performed on a subset of the TREC Genomics Track 2005 collection. Our approach includes an experimental set up to manually assess doc-2-doc relevance and the corresponding analysis done on the results obtained from this experiment. The experiment takes one document as a reference and assesses a second document regarding its relevance to the reference one. The consistency of the assessments done by 4 domain experts was evaluated. The lack of agreement between annotators may be due to: i) The abstract lacks key information and/or ii) Lack of experience of the annotators in the evaluation of some topics.
Während sich die unternehmerische Arbeitswelt immer mehr in Richtung Agilität verschiebt, verharrt das IT-Controlling noch in alten, klassischen Strukturen. Diese Arbeit untersucht die Fragestellung, ob und inwieweit agile Ansätze im IT-Controlling eingesetzt werden können. Dieser Beitrag ist eine modifizierte Version des in der Zeitschrift „HMD Praxis der Wirtschaftsinformatik“ (https://link.springer.com/article/10.1365/s40702-022-00837-0) erschienenen Artikels „Agiles IT-Controlling“.