A customised grammar framework for query classification
- Submitting institution
-
University of Portsmouth
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 14390110
- Type
- D - Journal article
- DOI
-
10.1016/j.eswa.2019.06.010
- Title of journal
- Expert Systems with Applications
- Article number
- -
- First page
- 164
- Volume
- 135
- Issue
- -
- ISSN
- 0957-4174
- Open access status
- Compliant
- Month of publication
- June
- Year of publication
- 2019
- 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
-
2
- Research group(s)
-
B - Computational Intelligence
- Citation count
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The new framework, which allows the incorporation of domain-specific knowledge and uses syntactic patterns to represent text, outperforms state-of-the-art methods. It was used for SMS spam identification (Mohasseb et al., WEBIST’20, 417-424) and in the analysis of consumer decision-making intents (Oltwater, MSc thesis, Univ. Twente, 2020).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -