{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T04:40:18Z","timestamp":1750308018908,"version":"3.41.0"},"reference-count":38,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2007,10,1]],"date-time":"2007-10-01T00:00:00Z","timestamp":1191196800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Inf. Syst."],"published-print":{"date-parts":[[2007,10]]},"abstract":"<jats:p>The rapid advancement of Internet technologies enables more and more educational institutes, companies, and government agencies to provide services, namely online services, through web portals. With hundreds of online services provided through a web portal, it is critical to design web portals, namely service portals, through which online services can be easily accessed by their consumers. This article addresses this critical issue from the perspective of service selection, that is, how to select a small number of service-links (i.e., hyperlinks pointing to online services) to be featured in the homepage of a service portal such that users can be directed to find the online services they seek most effectively. We propose a mathematically formulated metric to measure the effectiveness of the selected service-links in directing users to locate their desired online services and formally define the service selection problem. A solution method, ServiceFinder, is then proposed. Using real-world data obtained from the Utah State Government service portal, we show that ServiceFinder outperforms both the current practice of service selection and previous algorithms for adaptive website design. We also show that the performance of ServiceFinder is close to that of the optimal solution resulting from exhaustive search.<\/jats:p>","DOI":"10.1145\/1281485.1281488","type":"journal-article","created":{"date-parts":[[2007,10,12]],"date-time":"2007-10-12T15:47:29Z","timestamp":1192204049000},"page":"17","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["ServiceFinder"],"prefix":"10.1145","volume":"25","author":[{"given":"Xiao","family":"Fang","sequence":"first","affiliation":[{"name":"University of Toledo, Toledo, OH"}]},{"given":"Olivia R. Liu","family":"Sheng","sequence":"additional","affiliation":[{"name":"University of Utah, Salt Lake City, UT"}]},{"given":"Michael","family":"Chau","sequence":"additional","affiliation":[{"name":"The University of Hong Kong, Pokfulam, Hong Kong"}]}],"member":"320","published-online":{"date-parts":[[2007,10]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2005.99"},{"volume-title":"Proceedings of the 11th International Conference on Data Engineering","author":"Agrawal R.","key":"e_1_2_1_2_1"},{"volume-title":"Proceedings of the 17th International Joint Conference on Artificial Intelligence","author":"Anderson C.","key":"e_1_2_1_3_1"},{"volume-title":"Proceedings of the AAAI Spring Symposium on Information Gathering from Heterogeneous, Distributed Environments","author":"Armstrong R.","key":"e_1_2_1_4_1"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/245108.245124"},{"volume-title":"Proceedings of the 7th International World Wide Web Conference","author":"Brin S.","key":"e_1_2_1_6_1"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/0169-7552(95)00043-7"},{"key":"e_1_2_1_8_1","unstructured":"Center for Digital Government. 2003. Utah state portal ranks no. 1. http:\/\/www.centerdigitalgov.com\/center\/highlightstory.phtml?docid=69811.  Center for Digital Government. 2003. 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