Visual Analytics and Similarity Search: Concepts and Challenges for Effective Retrieval Considering Users, Tasks, and Data

D. Seebacher*, J. Häußler, M. Stein, H. Janetzko, T. Schreck, Daniel A. Keim

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


A major challenge of the contemporary information age is the overwhelming and increasing data amount, especially when looking for specific information. Searching for relevant information is no longer manually possible, but has to rely on automatic methods, specifically, similarity search. From a formal perspective, similarity search can be seen as the problem of finding entities, which are considered to be similar to a query with respect to certain describing features. The question which features or which weighted combination of features to use for a given query creates a need for semi-automatic methods to address the needs of diverse users. Furthermore, the quality of the results of a similarity search is more than effectiveness, measured by precision and recall. The user ideally needs to trust the results and understand how they were computed. We propose to apply Visual Analytics methodologies, for synergistic cooperation of user and algorithms, to integrate three key dimensions of similarity search: users, tasks, and data for effective search. However, there exists a gap in knowledge how user, task as well as the available data influence each other and the similarity search. In this concept paper, we envision how Visual Analytics can be used to tackle current challenges of similarity search.
Original languageEnglish
Title of host publicationInternational Conference on Similarity Search and Applications, SISAP 2017
ISBN (Electronic)978-3-319-68474-1
Publication statusPublished - 2017
Event10th International Conference on Similarity Search and Applications: SISAP 2017 - Munich, Germany
Duration: 4 Oct 20176 Oct 2017

Publication series

NameLecture Notes in Computer Science


Conference10th International Conference on Similarity Search and Applications

Fields of Expertise

  • Information, Communication & Computing

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