Weight-adjustable ranking for keyword search in relational satabases
Huge volumes of invaluable information are hidden behind web relational databases. They could not be extracted by search engines. The problem is especially severe for long text data, for example: book reviews, company descriptions, and product specifications. Many researches have investigated to in...
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my.sunway.eprints.16902021-03-29T03:02:04Z http://eprints.sunway.edu.my/1690/ Weight-adjustable ranking for keyword search in relational satabases Jou, Chichang. Lau, Sian Lun * QA76 Computer software Huge volumes of invaluable information are hidden behind web relational databases. They could not be extracted by search engines. The problem is especially severe for long text data, for example: book reviews, company descriptions, and product specifications. Many researches have investigated to integrate information retrieval and database indexing technologies to provide keyword search functionality for these useful contents. Due to diversifying data relationships in application domains and miscellaneous personal preferences, current ranking results of related researches do not satisfy user requirements. We design and implement a Weight-Adjustable Ranking for Keyword Search (WARKS) system to address the issue. Mean average precision (MAP) and mean rank reciprocal difference (MRRD) are proposed as measurements of ranking effectiveness. We use an integrated international trade show database as our experimental domain. User study demonstrates that WARKS performs better than previous practices. 2018 Conference or Workshop Item PeerReviewed text en cc_by_nc_4 http://eprints.sunway.edu.my/1690/1/Lau%20Sian%20Lun%20Weigh%20adjustable.pdf Jou, Chichang. and Lau, Sian Lun * (2018) Weight-adjustable ranking for keyword search in relational satabases. In: 2nd International Conference on Intelligent and Interactive Computing (IIC2018), 8-9 August 2018, Melaka, Malaysia. (Unpublished) |
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Huge volumes of invaluable information are hidden behind web relational databases. They could not be extracted by search engines. The problem is especially severe for long text data, for example: book reviews, company descriptions,
and product specifications. Many researches have investigated to integrate information retrieval and database indexing technologies to provide keyword
search functionality for these useful contents. Due to diversifying data relationships in application domains and miscellaneous personal preferences, current ranking results of related researches do not satisfy user requirements. We design and implement a Weight-Adjustable Ranking for Keyword Search (WARKS) system to address the issue. Mean average precision (MAP) and mean rank reciprocal
difference (MRRD) are proposed as measurements of ranking effectiveness. We use an integrated international trade show database as our experimental domain. User study demonstrates that WARKS performs better than previous
practices. |
format |
Conference or Workshop Item |
author |
Jou, Chichang. Lau, Sian Lun * |
author_facet |
Jou, Chichang. Lau, Sian Lun * |
author_sort |
Jou, Chichang. |
title |
Weight-adjustable ranking for keyword search in
relational satabases |
title_short |
Weight-adjustable ranking for keyword search in
relational satabases |
title_full |
Weight-adjustable ranking for keyword search in
relational satabases |
title_fullStr |
Weight-adjustable ranking for keyword search in
relational satabases |
title_full_unstemmed |
Weight-adjustable ranking for keyword search in
relational satabases |
title_sort |
weight-adjustable ranking for keyword search in
relational satabases |
publishDate |
2018 |
url |
http://eprints.sunway.edu.my/1690/1/Lau%20Sian%20Lun%20Weigh%20adjustable.pdf http://eprints.sunway.edu.my/1690/ |
_version_ |
1696978737945378816 |
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13.18916 |