| 书目名称 | WEBKDD 2002 - Mining Web Data for Discovering Usage Patterns and Profiles |
| 副标题 | 4th International Wo |
| 编辑 | Osmar R. Zaïane,Jaideep Srivastava,Brij Masand |
| 视频video | |
| 丛书名称 | Lecture Notes in Computer Science |
| 图书封面 |  |
| 描述 | 1 WorkshopTheme Data mining as a discipline aims to relate the analysis of large amounts of user data to shed light on key business questions. Web usage mining in particular, a relatively young discipline, investigates methodologies and techniques that - dress the unique challenges of discovering insights from Web usage data, aiming toevaluateWebusability,understandtheinterestsandexpectationsofusersand assess the e?ectiveness of content delivery. The maturing and expanding Web presents a key driving force in the rapid growth of electronic commerce and a new channel for content providers. Customized o?ers and content, made possible by discovered knowledge about the customer, are fundamental for the establi- ment of viable e-commerce solutions and sustained and e?ective content delivery in noncommercial domains. Rich Web logs provide companies with data about their online visitors and prospective customers, allowing microsegmentation and personalized interactions. While Web mining as a domain is several years old, the challenges that characterize data analysis in this area continue to be formidable. Though p- processing data routinely takes up a major part of the e?ort in data mining |
| 出版日期 | Conference proceedings 2003 |
| 关键词 | Alignment; Session; WWW; algorithms; association rule mining; clustering; data mining; knowledge discovery; |
| 版次 | 1 |
| doi | https://doi.org/10.1007/b11784 |
| isbn_softcover | 978-3-540-20304-9 |
| isbn_ebook | 978-3-540-39663-5Series ISSN 0302-9743 Series E-ISSN 1611-3349 |
| issn_series | 0302-9743 |
| copyright | Springer-Verlag Berlin Heidelberg 2003 |
发表于 2025-3-21 17:08:20
