Reference : Semantic and Interactive Search in an Advanced Note-Taking App for Learning Material
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/51355
Semantic and Interactive Search in an Advanced Note-Taking App for Learning Material
English
Atashpendar, Aryobarzan mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS) >]
Grevisse, Christian mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS) >]
Botev, Jean mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS) >]
Rothkugel, Steffen mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS) >]
Jun-2022
Proceedings of the 24th International Conference on Human-Computer Interaction (HCI International)
Springer
Yes
9th International Conference On Learning And Collaboration Technologies (LCT)
from 26-06-2022 to 01-07-2022
[en] Learning material ; Semantic search ; Question-answering ; Note similarity ; Interactive search
[en] Note-taking apps on tablets are increasingly becoming the go-to space for managing learning material as a student. In particular, digital note-taking presents certain advantages over traditional pen-and-paper approaches when it comes to organizing and retrieving a library of notes thanks to various search functionalities. This paper presents improvements to the classic textual-input-based search field, by introducing a semantic search that considers the meaning of a user’s search terms and an automatic question-answering process that extracts the answer to the user’s question from their notes for more efficient information retrieval. Additionally, visual methods for finding specific notes are proposed, which do not require the input of text by the user: through the integration of a semantic similarity metric, notes similar to a selected document can be displayed based on common topics. Furthermore, a fully interactive process allows one to search for notes by selecting different types of dynamically generated filters, thus eliminating the need for textual input. Finally, a graph-based visualization is explored for the search results, which clusters semantically similar notes closer together to relay additional information to the user besides the raw search results.
http://hdl.handle.net/10993/51355
10.1007/978-3-031-05657-4_2

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