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

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BEECKS, Christian, ed. and others. Similarity Search and Applications. Cham: Springer, 2017, pp. 324-332. Lecture Notes in Computer Science. 10609. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-319-68473-4. Available under: doi: 10.1007/978-3-319-68474-1_23
Zusammenfassung

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.

Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
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Similarity search, Recommender systems, Visual analytics
Konferenz
10th International Conference, SISAP 2017, 4. Okt. 2017 - 6. Okt. 2017, Munich, Germany
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Zitieren
ISO 690SEEBACHER, Daniel, Johannes HÄUSSLER, Manuel STEIN, Halldor JANETZKO, Tobias SCHRECK, 2017. Visual Analytics and Similarity Search : Concepts and Challenges for Effective Retrieval Considering Users, Tasks, and Data. 10th International Conference, SISAP 2017. Munich, Germany, 4. Okt. 2017 - 6. Okt. 2017. In: BEECKS, Christian, ed. and others. Similarity Search and Applications. Cham: Springer, 2017, pp. 324-332. Lecture Notes in Computer Science. 10609. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-319-68473-4. Available under: doi: 10.1007/978-3-319-68474-1_23
BibTex
@inproceedings{Seebacher2017Visua-41299,
  year={2017},
  doi={10.1007/978-3-319-68474-1_23},
  title={Visual Analytics and Similarity Search : Concepts and Challenges for Effective Retrieval Considering Users, Tasks, and Data},
  number={10609},
  isbn={978-3-319-68473-4},
  issn={0302-9743},
  publisher={Springer},
  address={Cham},
  series={Lecture Notes in Computer Science},
  booktitle={Similarity Search and Applications},
  pages={324--332},
  editor={Beecks, Christian},
  author={Seebacher, Daniel and Häußler, Johannes and Stein, Manuel and Janetzko, Halldor and Schreck, Tobias}
}
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