1995
DOI: 10.1002/(sici)1097-4571(199509)46:8<562::aid-asi2>3.0.co;2-b
|View full text |Cite
|
Sign up to set email alerts
|

The retrieval effectiveness of five clustering algorithms as a function of indexing exhaustivity

Abstract: The retrieval effectiveness of five hierarchical clustering methods (single link, complete link, group average, Ward's method, and weighted average) is examined as a function of indexing exhaustivity with four test collections (CF, Cranfield, Medlars, and Time). Evaluations of retrieval effectiveness, based on three measures of optimal retrieval performance, confirm earlier findings that the performance of a retrieval system based on single‐link clustering varies as a function of indexing exhaustively but fail… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

3
15
0

Year Published

1997
1997
2011
2011

Publication Types

Select...
8
1

Relationship

1
8

Authors

Journals

citations
Cited by 26 publications
(18 citation statements)
references
References 10 publications
(18 reference statements)
3
15
0
Order By: Relevance
“…4. Another research direction is definition of document vectors with different levels of indexing exhaustivity [Burgin, 1995] or by latent semantic indexing (LSI) and measuring the system performance [Lee, 1997;Schütze, Silverstein, 1997].…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…4. Another research direction is definition of document vectors with different levels of indexing exhaustivity [Burgin, 1995] or by latent semantic indexing (LSI) and measuring the system performance [Lee, 1997;Schütze, Silverstein, 1997].…”
Section: Discussionmentioning
confidence: 99%
“…Most clustering research in IR is related to cluster search effectiveness [Griffiths et al, 1986;Willett, 1988;Burgin 1995;Shaw et al 1997;Schütze, Craig 1997]. The research on efficiency aspects of cluster searches is limited.…”
Section: Previous and Related Workmentioning
confidence: 99%
“…Hierarchical clustering algorithms have been intensively studied as well as neural network models. Several methods are used as Support vector machines, Naïve Bayes or Neural networks [11], where Naïve Bayes outperforms the others [2].…”
Section: Classification Taskmentioning
confidence: 99%
“…Specifically, we adopt the complete-linkage HAC method, which is known to produce tightly bound and compact clusters (Burgin, 1995) even though other types of HAC clustering algorithms such as Ward's method (El-Hamdouchi and Willett, 1986) and average-group method (Voorhees, 1986) can also be used. Another common way of clustering, namely partitional clustering, is possible.…”
Section: User-constrained Document Clustering (Document Clustering Momentioning
confidence: 99%