Special issue: "Web retrieval and mining"
| dc.contributor.author | Chen, Hsinchun | |
| dc.date.accessioned | 2004-08-16T00:00:01Z | |
| dc.date.available | 2010-06-18T23:39:46Z | |
| dc.date.issued | 2003-04 | en_US |
| dc.date.submitted | 2004-08-16 | en_US |
| dc.identifier.citation | Special issue: "Web retrieval and mining" 2003-04, 35(1):1-5 Decision Support Systems | en_US |
| dc.identifier.uri | http://hdl.handle.net/10150/106101 | |
| dc.description | Artificial Intelligence Lab, Department of MIS, University of Arizona | en_US |
| dc.description.abstract | Search engines and data mining are two research areas that have experienced significant progress over the past few years. Overwhelming acceptance of the Internet as a primary medium for content delivery and business transactions has created unique opportunities and challenges for researchers. The richness of the webâ s multimedia content, the reach and timeliness of web-based publication, the proliferation of e-commerce activities and the potential for wireless web delivery have generated many interesting research problems. Technical, system, organizational and social research approaches are all needed to address these research problems. Many interesting webretrieval and mining research topics have emerged recently. These include, but are not limited to, the following: text and data mining on the web, web visualization, web intelligence and agents, web-based decision support and knowledge management, wireless web retrieval and visualization, web-based usability methodology, web-based analysis for eCommerce applications. This special issue consists of nine papers that report research in web retrieval and mining. | |
| dc.format.mimetype | application/pdf | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Elsevier | en_US |
| dc.subject | Web Mining | en_US |
| dc.subject | World Wide Web | en_US |
| dc.subject.other | National Science Digital Library | en_US |
| dc.subject.other | NDSL | en_US |
| dc.subject.other | Artificial intelligence lab | en_US |
| dc.subject.other | AI lab | en_US |
| dc.subject.other | Information retrieval | en_US |
| dc.title | Special issue: "Web retrieval and mining" | en_US |
| dc.type | Journal Article (Paginated) | en_US |
| dc.identifier.journal | Decision Support Systems | en_US |
| refterms.dateFOA | 2018-04-26T18:09:41Z | |
| html.description.abstract | Search engines and data mining are two research areas that have experienced significant progress over the past few years. Overwhelming acceptance of the Internet as a primary medium for content delivery and business transactions has created unique opportunities and challenges for researchers. The richness of the webâ s multimedia content, the reach and timeliness of web-based publication, the proliferation of e-commerce activities and the potential for wireless web delivery have generated many interesting research problems. Technical, system, organizational and social research approaches are all needed to address these research problems. Many interesting webretrieval and mining research topics have emerged recently. These include, but are not limited to, the following: text and data mining on the web, web visualization, web intelligence and agents, web-based decision support and knowledge management, wireless web retrieval and visualization, web-based usability methodology, web-based analysis for eCommerce applications. This special issue consists of nine papers that report research in web retrieval and mining. |
