Name
Abstract | ||
|---|---|---|
User interest in topics and resources is known to be recurrent and to follow specific patterns, depending on the type of topic or resource. Traditional methods for predicting reoccurring patterns are based on ranking and associative models. In this paper we identify several 'canonical' patterns by clustering keywords related to visited resources, making use of a large repository of Web usage data. The keywords are derived from a 'virtual' folksonomy of tags assigned to these resources using a collaborative bookmarking system. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/1998076.1998095 | JCDL |
Keywords | Field | DocType |
virtual folksonomy,traditional method,clustering keyword,large repository,user interest pattern,web usage data,user interest,associative model,collaborative bookmarking system,specific pattern,reoccurring pattern | World Wide Web,Associative property,Information retrieval,Ranking,Computer science,Folksonomy,Web usage data,Cluster analysis,Bookmarking | Conference |
Citations | PageRank | References |
4 | 0.52 | 14 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ricardo Kawase | 1 | 57 | 6.34 |
| Eelco Herder | 2 | 586 | 55.28 |