XPathia: A Deep Learning Approach for Translating Natural Language into XPath Queries for Non-Technical Users
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| Pubblicato in: | International Journal of Advanced Computer Science and Applications vol. 16, no. 6 (2025) |
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| Autore principale: | |
| Pubblicazione: |
Science and Information (SAI) Organization Limited
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| Soggetti: | |
| Accesso online: | Citation/Abstract Full Text - PDF |
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| 024 | 7 | |a 10.14569/IJACSA.2025.01606102 |2 doi | |
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| 245 | 1 | |a XPathia: A Deep Learning Approach for Translating Natural Language into XPath Queries for Non-Technical Users | |
| 260 | |b Science and Information (SAI) Organization Limited |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a XPath is a widely used language for navigating and extracting data from XML documents due to its simple syntax and powerful querying capabilities. However, non-technical users often struggle to retrieve the needed information from XML files, as they lack knowledge of XML structures and query languages like XPath. To address this challenge, we propose XPathia, a novel deep learning-based model that automatically translates natural language questions into corresponding XPath queries. Our approach employs supervised learning on an annotated XML dataset to learn accurate mappings between natural language and structured XPath expressions. We evaluate XPathia using two standard metrics: Component Matching (CM) and Exact Matching (EM). Experimental results demonstrate that XPathia achieves a state-of-the-art performance with an accuracy of 25.85% on the test set. | |
| 653 | |a Translating | ||
| 653 | |a Matching | ||
| 653 | |a Deep learning | ||
| 653 | |a Queries | ||
| 653 | |a Information retrieval | ||
| 653 | |a Extensible Markup Language | ||
| 653 | |a Supervised learning | ||
| 653 | |a Query languages | ||
| 653 | |a Language | ||
| 653 | |a Text categorization | ||
| 653 | |a Datasets | ||
| 653 | |a Computer science | ||
| 653 | |a Syntax | ||
| 653 | |a Relevance | ||
| 653 | |a Data base management systems | ||
| 653 | |a Natural language processing | ||
| 653 | |a Documents | ||
| 773 | 0 | |t International Journal of Advanced Computer Science and Applications |g vol. 16, no. 6 (2025) | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3231644821/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3231644821/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |