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Semantic and Interactive Search in an Advanced Note-Taking App for Learning Material

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Part of the Lecture Notes in Computer Science book series (LNCS,volume 13328)

Abstract

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.

Keywords

  • Learning material
  • Semantic search
  • Question-answering
  • Note similarity
  • Interactive search

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Atashpendar, A., Grévisse, C., Botev, J., Rothkugel, S. (2022). Semantic and Interactive Search in an Advanced Note-Taking App for Learning Material. In: Zaphiris, P., Ioannou, A. (eds) Learning and Collaboration Technologies. Designing the Learner and Teacher Experience. HCII 2022. Lecture Notes in Computer Science, vol 13328. Springer, Cham. https://doi.org/10.1007/978-3-031-05657-4_2

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  • DOI: https://doi.org/10.1007/978-3-031-05657-4_2

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