Learning search pattern for construction procurement using keyword net

Ren-Jye Dzeng, Shyh Shiuh Wang

研究成果: Conference contribution

摘要

As more and more procurement websites become available on the Internet, seeking information from websites has become an essential part of a contractor's procurement undertaking. Several e-markets, specifically for construction, have also been established, including bLiquid.com and ProcureZone. However, most websites provide only two primary ways of searching for information, namely by index/menu or by keyword. Instead of relying on the primitive search engines found in most procurement websites, a search guide system could help a user's keyword search by reducing the number of keywords required to find the desired information. Our research recognized that professional procurement experience helped users more effectively carry out website information searches, by using fewer keywords. We planned to capture such experience in order to guide inexperienced users in their search. The research goal was to improve search effectiveness by guiding the user's search using three approaches; namely correction, specification and extension. Based on these three approaches, this research applied the following guides: correction; specification-by-equivalence; specification-by-detail; extension-by-time; extension-by-location; extension-by-team; and extension-by-component. The paper will describe how we classified users for learning credibility, and the learning framework for recording expert users' search patterns. Twelve professionals, using 14 procurement packages, with 64 items in total, evaluated the proposed framework. It will be demonstrated that the proposed learning keyword guide facilitated a dynamic, customized menu and indexing system, and reduced the number of keywords required for the professionals to find the information they desired.

原文English
主出版物標題Artificial Intelligence Applications and Innovations - FIP TCI2 WG12.5 - 2nd IFIP Conference on Artificial Intelligence Applications and Innovations, AIAI 2005
發行者Springer New York LLC
頁面69-78
頁數10
ISBN(列印)9780387283180
DOIs
出版狀態Published - 1 一月 2005
事件IFIP TCI2 WG12.5 2nd IFIP Conference on Artificial Intelligence Applications and Innovations, AIAI 2005 - Beijing, China
持續時間: 7 九月 20059 九月 2005

出版系列

名字IFIP Advances in Information and Communication Technology
187
ISSN(列印)1868-4238

Conference

ConferenceIFIP TCI2 WG12.5 2nd IFIP Conference on Artificial Intelligence Applications and Innovations, AIAI 2005
國家China
城市Beijing
期間7/09/059/09/05

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  • 引用此

    Dzeng, R-J., & Wang, S. S. (2005). Learning search pattern for construction procurement using keyword net. 於 Artificial Intelligence Applications and Innovations - FIP TCI2 WG12.5 - 2nd IFIP Conference on Artificial Intelligence Applications and Innovations, AIAI 2005 (頁 69-78). (IFIP Advances in Information and Communication Technology; 卷 187). Springer New York LLC. https://doi.org/10.1007/0-387-29295-0_8