Ontology mining for personalized search
Edited book (chapter)
| Chapter Title | Ontology mining for personalized search |
|---|---|
| Book Chapter Category | Edited book (chapter) |
| ERA Publisher ID | 3337 |
| Book Title | Data mining for business applications |
| Authors | Li, Yuefeng (Author) and Tao, Xiaohui (Author) |
| Editors | Cao, Longbing, Yu, Philip S., Zhang, Chengqi and Zhang, Huaifeng |
| Page Range | 63-78 |
| Chapter Number | 5 |
| Number of Pages | 16 |
| Year | 2009 |
| Publisher | Springer |
| Place of Publication | New York, NY. United States |
| ISBN | 9780387794198 |
| 9780387794204 | |
| Digital Object Identifier (DOI) | https://doi.org/10.1007/978-0-387-79420-4_5 |
| Web Address (URL) | http://download.springer.com/static/pdf/390/chp%253A10.1007%252F978-0-387-79420-4_5.pdf?auth66=1416372036_35642d43bf760610e3995934adf72756&ext=.pdf |
| Abstract | Knowledge discovery for user information needs in user local information repositories is a challenging task. Traditional data mining techniques cannot provide a satisfactory solution for this challenge, because there exists a lot of uncertainties in the local information repositories. In this chapter, we introduce ontology mining, |
| Keywords | knowledge-based information gathering; local instance repository; ontology; user background knowledge; user information needs; world knowledge base |
| ANZSRC Field of Research 2020 | 460903. Information modelling, management and ontologies |
| 469999. Other information and computing sciences not elsewhere classified | |
| 460508. Information retrieval and web search | |
| Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
| Byline Affiliations | Queensland University of Technology |
| Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q102q/ontology-mining-for-personalized-search
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