Data Visualization with Structural Control of Global Cohort and Local Data Neighborhoods
- Submitting institution
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The University of Liverpool
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 12085
- Type
- D - Journal article
- DOI
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10.1109/TPAMI.2017.2715806
- Title of journal
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Article number
- -
- First page
- 1323
- Volume
- 40
- Issue
- 6
- ISSN
- 0162-8828
- Open access status
- Compliant
- Month of publication
- June
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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2
- Research group(s)
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-
- Citation count
- 5
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The techniques developed in this paper are applied in a KTP project (KTP12390, £300K) with Thornton & Lowe Ltd on advanced information retrieval and visualisation for tender and bid management systems. The result from the paper on accurately preserving desired information in embedding space has found various applications, for example, in "Cross-Domain Sentiment Encoding through Stochastic Word Embedding" (Goulermas et al, TKDE 2020).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -