Spacewalker: Traversing Representation Spaces for Fast Interactive Exploration and Annotation of Unstructured Data
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arXiv
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| Autori principali: | , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866915101799350272 |
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| author | Heine, Lukas Hörst, Fabian Fragemann, Jana Luijten, Gijs Egger, Jan Bahnsen, Fin Sarfraz, M. Saquib Kleesiek, Jens Seibold, Constantin |
| author_facet | Heine, Lukas Hörst, Fabian Fragemann, Jana Luijten, Gijs Egger, Jan Bahnsen, Fin Sarfraz, M. Saquib Kleesiek, Jens Seibold, Constantin |
| contents | In industries such as healthcare, finance, and manufacturing, analysis of unstructured textual data presents significant challenges for analysis and decision making. Uncovering patterns within large-scale corpora and understanding their semantic impact is critical, but depends on domain experts or resource-intensive manual reviews. In response, we introduce Spacewalker in this system demonstration paper, an interactive tool designed to analyze, explore, and annotate data across multiple modalities. It allows users to extract data representations, visualize them in low-dimensional spaces and traverse large datasets either exploratory or by querying regions of interest. We evaluated Spacewalker through extensive experiments and annotation studies, assessing its efficacy in improving data integrity verification and annotation. We show that Spacewalker reduces time and effort compared to traditional methods. The code of this work is open-source and can be found at: https://github.com/code-lukas/Spacewalker |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_16793 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Spacewalker: Traversing Representation Spaces for Fast Interactive Exploration and Annotation of Unstructured Data Heine, Lukas Hörst, Fabian Fragemann, Jana Luijten, Gijs Egger, Jan Bahnsen, Fin Sarfraz, M. Saquib Kleesiek, Jens Seibold, Constantin Computer Vision and Pattern Recognition Human-Computer Interaction Information Retrieval In industries such as healthcare, finance, and manufacturing, analysis of unstructured textual data presents significant challenges for analysis and decision making. Uncovering patterns within large-scale corpora and understanding their semantic impact is critical, but depends on domain experts or resource-intensive manual reviews. In response, we introduce Spacewalker in this system demonstration paper, an interactive tool designed to analyze, explore, and annotate data across multiple modalities. It allows users to extract data representations, visualize them in low-dimensional spaces and traverse large datasets either exploratory or by querying regions of interest. We evaluated Spacewalker through extensive experiments and annotation studies, assessing its efficacy in improving data integrity verification and annotation. We show that Spacewalker reduces time and effort compared to traditional methods. The code of this work is open-source and can be found at: https://github.com/code-lukas/Spacewalker |
| title | Spacewalker: Traversing Representation Spaces for Fast Interactive Exploration and Annotation of Unstructured Data |
| topic | Computer Vision and Pattern Recognition Human-Computer Interaction Information Retrieval |
| url | https://arxiv.org/abs/2409.16793 |