Improving Search Query Accuracy for Specialized Websites Through Intelligent Text Correction and Reconstruction Models
In the digital era, the need for precise and efficient search operations is paramount as users increasingly rely on online resources to access specific information. However, search accuracy is often hindered by errors in user queries, such as incomplete or degraded input. Errors in search queries ca...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-11-01
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| Series: | Information |
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| Online Access: | https://www.mdpi.com/2078-2489/15/11/683 |
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| author | Dana Simian Marin-Eusebiu Șerban |
| author_facet | Dana Simian Marin-Eusebiu Șerban |
| author_sort | Dana Simian |
| collection | DOAJ |
| description | In the digital era, the need for precise and efficient search operations is paramount as users increasingly rely on online resources to access specific information. However, search accuracy is often hindered by errors in user queries, such as incomplete or degraded input. Errors in search queries can reduce both the precision and speed of search results, making error correction a key factor in enhancing the user experience. This paper addresses the challenge of improving search performance through query error correction. We propose a novel methodology and architecture aimed at optimizing search results across thematic websites, such as those for universities, hospitals, or tourism agencies. The proposed solution leverages an intelligent model based on Gated Recurrent Units (GRUs) and Bahdanau Attention mechanisms to reconstruct erroneous or incomplete text in search queries. To validate our approach, we embedded the model in a prototype website consolidating data from multiple universities, demonstrating significant improvements in search accuracy and efficiency. |
| format | Article |
| id | doaj-art-e8f5c5b593f042efab56e49f8d418611 |
| institution | Kabale University |
| issn | 2078-2489 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj-art-e8f5c5b593f042efab56e49f8d4186112024-11-26T18:06:33ZengMDPI AGInformation2078-24892024-11-01151168310.3390/info15110683Improving Search Query Accuracy for Specialized Websites Through Intelligent Text Correction and Reconstruction ModelsDana Simian0Marin-Eusebiu Șerban1Faculty of Sciences, Research Center in Informatics and Information Technology, Lucian Blaga University of Sibiu, 550012 Sibiu, RomaniaFaculty of Sciences, Research Center in Informatics and Information Technology, Lucian Blaga University of Sibiu, 550012 Sibiu, RomaniaIn the digital era, the need for precise and efficient search operations is paramount as users increasingly rely on online resources to access specific information. However, search accuracy is often hindered by errors in user queries, such as incomplete or degraded input. Errors in search queries can reduce both the precision and speed of search results, making error correction a key factor in enhancing the user experience. This paper addresses the challenge of improving search performance through query error correction. We propose a novel methodology and architecture aimed at optimizing search results across thematic websites, such as those for universities, hospitals, or tourism agencies. The proposed solution leverages an intelligent model based on Gated Recurrent Units (GRUs) and Bahdanau Attention mechanisms to reconstruct erroneous or incomplete text in search queries. To validate our approach, we embedded the model in a prototype website consolidating data from multiple universities, demonstrating significant improvements in search accuracy and efficiency.https://www.mdpi.com/2078-2489/15/11/683text correctionmachine learningsearch optimization |
| spellingShingle | Dana Simian Marin-Eusebiu Șerban Improving Search Query Accuracy for Specialized Websites Through Intelligent Text Correction and Reconstruction Models Information text correction machine learning search optimization |
| title | Improving Search Query Accuracy for Specialized Websites Through Intelligent Text Correction and Reconstruction Models |
| title_full | Improving Search Query Accuracy for Specialized Websites Through Intelligent Text Correction and Reconstruction Models |
| title_fullStr | Improving Search Query Accuracy for Specialized Websites Through Intelligent Text Correction and Reconstruction Models |
| title_full_unstemmed | Improving Search Query Accuracy for Specialized Websites Through Intelligent Text Correction and Reconstruction Models |
| title_short | Improving Search Query Accuracy for Specialized Websites Through Intelligent Text Correction and Reconstruction Models |
| title_sort | improving search query accuracy for specialized websites through intelligent text correction and reconstruction models |
| topic | text correction machine learning search optimization |
| url | https://www.mdpi.com/2078-2489/15/11/683 |
| work_keys_str_mv | AT danasimian improvingsearchqueryaccuracyforspecializedwebsitesthroughintelligenttextcorrectionandreconstructionmodels AT marineusebiuserban improvingsearchqueryaccuracyforspecializedwebsitesthroughintelligenttextcorrectionandreconstructionmodels |