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https://doi.org/10.21256/zhaw-3485| Publikationstyp: | Beitrag in wissenschaftlicher Zeitschrift |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | A study of untrained models for multimodal information retrieval |
| Autor/-in: | Imhof, Melanie Braschler, Martin |
| DOI: | 10.1007/s10791-017-9322-x 10.21256/zhaw-3485 |
| Erschienen in: | Information Retrieval Journal |
| Band(Heft): | 21 |
| Heft: | 1 |
| Seite(n): | 81 |
| Seiten bis: | 106 |
| Erscheinungsdatum: | 3-Nov-2017 |
| Verlag / Hrsg. Institution: | Springer |
| ISSN: | 1386-4564 1573-7659 |
| Sprache: | Englisch |
| Fachgebiet (DDC): | 020: Bibliotheks- und Informationswissenschaft |
| Zusammenfassung: | Operational multimodal information retrieval systems have to deal with increasingly complex document collections and queries that are composed of a large set of textual and non-textual modalities such as ratings, prices, timestamps, geographical coordinates, etc. The resulting combinatorial explosion of modality combinations makes it intractable to treat each modality individually and to obtain suitable training data. As a consequence, instead of finding and training new models for each individual modality or combination of modalities, it is crucial to establish unified models, and fuse their outputs in a robust way. Since the most popular weighting schemes for textual retrieval have in the past generalized well to many retrieval tasks, we demonstrate how they can be adapted to be used with non-textual modalities, which is a first step towards finding such a unified model. We demonstrate that the popular weighting scheme BM25 is suitable to be used for multimodal IR systems and analyze the underlying assumptions of the BM25 formula with respect to merging modalities under the so-called raw-score merging hypothesis, which requires no training. We establish a multimodal baseline for two multimodal test collections, show how modalities differ with respect to their contribution to relevance and the difficulty of treating modalities with overlapping information. Our experiments demonstrate that our multimodal baseline with no training achieves a significantly higher retrieval effectiveness than using just the textual modality for the social book search 2016 collection and lies in the range of a trained multimodal approach using the optimal linear combination of the modality scores. |
| Weitere Angaben: | Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch) |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/2169 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | Lizenz gemäss Verlagsvertrag |
| Gesperrt bis: | 2023-01-01 |
| Departement: | School of Engineering |
| Organisationseinheit: | Institut für Informatik (InIT) |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 10.1007_s10791-017-9322-x.pdf | 446.22 kB | Adobe PDF |  Öffnen/Anzeigen |
Zur Langanzeige
Imhof, M., & Braschler, M. (2017). A study of untrained models for multimodal information retrieval. Information Retrieval Journal, 21(1), 81–106. https://doi.org/10.1007/s10791-017-9322-x
Imhof, M. and Braschler, M. (2017) ‘A study of untrained models for multimodal information retrieval’, Information Retrieval Journal, 21(1), pp. 81–106. Available at: https://doi.org/10.1007/s10791-017-9322-x.
M. Imhof and M. Braschler, “A study of untrained models for multimodal information retrieval,” Information Retrieval Journal, vol. 21, no. 1, pp. 81–106, Nov. 2017, doi: 10.1007/s10791-017-9322-x.
IMHOF, Melanie und Martin BRASCHLER, 2017. A study of untrained models for multimodal information retrieval. Information Retrieval Journal. 3 November 2017. Bd. 21, Nr. 1, S. 81–106. DOI 10.1007/s10791-017-9322-x
Imhof, Melanie, and Martin Braschler. 2017. “A Study of Untrained Models for Multimodal Information Retrieval.” Information Retrieval Journal 21 (1): 81–106. https://doi.org/10.1007/s10791-017-9322-x.
Imhof, Melanie, and Martin Braschler. “A Study of Untrained Models for Multimodal Information Retrieval.” Information Retrieval Journal, vol. 21, no. 1, Nov. 2017, pp. 81–106, https://doi.org/10.1007/s10791-017-9322-x.
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