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Auflistung nach Schlagwort "Semantic Search"

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  • Konferenzbeitrag
    Semantic Search for Biological Datasets: A Usability Study on Modes of Querying and Explaining Search Results
    (BTW 2023, 2023) Löffler, Felicitas; Shafiei, Fateme; Witte, René; König-Ries, Birgitta; Klan, Friederike
    Dataset discovery is a frequent task in daily research practice, yet studies are missing that explore the usability of user interfaces (UI) in data portals. In particular, very few user studies exist that analyze whether particular elements in the user interface are useful for search tasks. We aim to address those needs for more specific usability evaluations in dataset search. In this work, wepresent a flexible semantic search over biological datasets with two user interfaces. The search result contains semantically related terms, such as synonyms or more specific terms, obtained from domain ontologies. We evaluated the system in a user study with 20 scholars. We focused on two components, the query input to explore a search in categories (entity types) in comparision to a single input field, and we analyzed textual highlightings in the returned datasets to study whether users are distracted by semantic information such as URIs. Our results show that users prefer interfaces with a single input field for search tasks they are not familiar with, and that users appreciate explanations with terminologies and URIs.
  • Textdokument
    Using Knowledge Graphs to Manage a Data Lake
    (INFORMATIK 2020, 2021) Dibowski, Henrik; Schmid, Stefan
    Knowledge graphs as fundamental pillar of artificial intelligence are experiencing a strong demand. In contrast to machine learning and deep learning, knowledge graphs do not require large amounts of (training) data and offer a bigger potential for a multitude of domains and problems. This article shows the application of knowledge graphs for the semantic description and management of data in a data lake, which improves the findability and reusability of data, and enables the automatic processing by algorithms. Since knowledge graphs contain both the data as well as its semantically described schema (ontology), they enable novel ontology-driven software architectures, in which the domain knowledge and business logic can completely reside on the knowledge graph level. This article further introduces such a use case: an ontology-driven frontend implementation, which is able to fully adapt itself based on the underlying knowledge graph schema and dynamically render information in the desired manner.