Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/39797
DC Field | Value | Language |
---|---|---|
dc.contributor | 國立政治大學資訊科學系 | en_US |
dc.creator | 沈錳坤 | zh_TW |
dc.creator | Shan, Man-Kwan | - |
dc.date | 2005-09 | en_US |
dc.date.accessioned | 2010-05-27T08:50:43Z | - |
dc.date.available | 2010-05-27T08:50:43Z | - |
dc.date.issued | 2010-05-27T08:50:43Z | - |
dc.identifier.uri | http://nccur.lib.nccu.edu.tw/handle/140.119/39797 | - |
dc.description.abstract | Online, single-pass mining Web click streams poses some interesting computational issues, such as unbounded length of streaming data, possibly very fast arrival rate, and just one scan over previously arrived click-sequences. In this paper, we propose a new, single-pass algorithm, called DSM-TKP (Data Stream Mining for Top-K Path traversal patterns), for mining top-k path traversal patterns, where k is the desired number of path traversal patterns to be mined. An effective summary data structure called TKP-forest (Top-K Path forest) is used to maintain the essential information about the top-k path traversal patterns of the click-stream so far. Experimental studies show that DSM-TKP algorithm uses stable memory usage and makes only one pass over the streaming data. | - |
dc.language | en-US | en_US |
dc.language.iso | en_US | - |
dc.relation | 2005 IEEE/WIC/ACM International Conference on Web Intelligence | en_US |
dc.subject | DSM-TKP;Mining;Top-K Path Traversal Patterns;Web Click-Streams | en_US |
dc.title | DSM-TKP: Mining Top-K Path Traversal Patterns over Web Click-Streams | en_US |
dc.type | conference | en |
dc.identifier.doi | 10.1109/WI.2005.56 | en_US |
dc.doi.uri | http://dx.doi.org/10.1109/WI.2005.56 | en_US |
item.fulltext | With Fulltext | - |
item.grantfulltext | open | - |
item.languageiso639-1 | en_US | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
item.openairetype | conference | - |
Appears in Collections: | 會議論文 |
Files in This Item:
File | Description | Size | Format | |
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326-329.pdf | 122.6 kB | Adobe PDF2 | View/Open |
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