Search

Copyright of Automatisierungstechnik is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Google Knowledge Panels are information boxes in Google that display summarized information regarding a made search request in the search results, using information from the Google Knowledge Graph. This feature is usually displayed for questions or searches for entities and is intended to allow users to find relevant information more easily and quickly. What are the different types of Google Knowledge Panels? How is this function and its content perceived by users? In this study, the Google Knowledge Panel is evaluated in terms of system quality and content quality from the user's perspective. The Information Service Evaluation (ISE) model was adapted to match the Google Knowledge Panel and serves as a theoretical basis for the development of a survey. Results of the survey with 133 participants show that the users' expectations for an optimal information field within an information retrieval system mostly coincide with the experiences made regarding the Google Knowledge Panel. The Google Knowledge Panel does not meet the expectations of users for the following aspects: credibility, trust, timeliness, and objectivity. Further research is needed to find appropriate reasoning for the experienced differences and to make suitable suggestions to adapt the Google Knowledge Panel to the users' needs. [ABSTRACT FROM AUTHOR]

In einem Pilotprojekt hat das Staatsarchiv des Kantons Zürich den Bestand der Zürcher Ehedaten des 16.–18. Jahrhunderts mittels Semantic-Web-Technologien als Wissensnetz aufbereitet. Dabei wurden aus dem swissuniversities Projekt NIE-INE entwickelte Ansätze und Erkenntnisse aufgegriffen und ein modulares Verfahren entwickelt, bei dem Anwendungsfall für Anwendungsfall implementiert wird und an dessen Ende immer ein konsistentes und kontrollierbares Wissensrepräsentationssystem aus Ontologien und Graphdaten steht. In a pilot project, the Zurich State Archives transformed the holdings of Zurich's sixteenth to eighteenth century marriage data into a knowledge graph using Semantic Web technologies. In the process, approaches and findings developed from the swissuniversities' NIE-INE project were taken up and a modular procedure was developed, in which use case after use case is implemented and at the end of which there is always a consistent and controllable knowledge representation system of ontologies and graph data. [ABSTRACT FROM AUTHOR]

AI for AEC The article surveys current methods of data integration, artificial intelligence (AI), optimization, and control and their (potential) applications in architecture, engineering and construction. The survey includes symbolic AI‐methods as well as subsymbolic AI methods, i. e., machine learning. The article presents these methods in the context of applications that provide insight into current research projects at the Cluster of Excellence "Integrative Computational Design and Construction for Architecture" (IntCDC) at the University of Stuttgart: (1) Data integration to link data silos in design and construction processes, (2) knowledge graphs to represent knowledge in multidisciplinary design processes, (3) automated planning for scheduling and distribution of construction tasks, (4) supervised learning to estimate the results of expensive building simulations such as operational energy or of the behavior of natural materials such as wood, (5) unsupervised learning to visualize optimization results, (6) reinforcement learning for building with fibers and bamboo, and (8) control for construction robotics. The article concludes that integrative computational design and construction requires the cooperation of humans, material, and machines, and that AI – instead of merely automating design and construction processes – can moderate this cooperation. [ABSTRACT FROM AUTHOR]

Copyright of Zeitschrift für Bibliothekswesen und Bibliographie is the property of Vittorio Klostermann and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of HMD: Praxis der Wirtschaftsinformatik is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)