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DE-627 |
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20231223074311.0 |
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tu |
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231223s2005 xx ||||| 00| ||eng c |
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|a (DE-627)NLM156508338
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|a (NLM)16013756
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|a DE-627
|b ger
|c DE-627
|e rakwb
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| 041 |
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|a eng
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| 100 |
1 |
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|a Torsello, Andrea
|e verfasserin
|4 aut
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| 245 |
1 |
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|a Polynomial-time metrics for attributed trees
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|c 2005
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| 336 |
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|a Text
|b txt
|2 rdacontent
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| 337 |
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|a ohne Hilfsmittel zu benutzen
|b n
|2 rdamedia
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| 338 |
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|a Band
|b nc
|2 rdacarrier
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| 500 |
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|a Date Completed 11.08.2005
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|a Date Revised 10.12.2019
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|a published: Print
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|a Citation Status MEDLINE
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| 520 |
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|a We address the problem of comparing attributed trees and propose four novel distance measures centered around the notion of a maximal similarity common subtree. The proposed measures are general and defined on trees endowed with either symbolic or continuous-valued attributes and can be applied to rooted as well as unrooted trees. We prove that our measures satisfy the metric constraints and provide a polynomial-time algorithm to compute them. This is a remarkable and attractive property, since the computation of traditional edit-distance-based metrics is, in general, NP-complete, at least in the unordered case. We experimentally validate the usefulness of our metrics on shape matching tasks and compare them with (an approximation of) edit-distance
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|a Comparative Study
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| 650 |
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|a Evaluation Study
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| 650 |
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|a Journal Article
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| 650 |
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|a Research Support, Non-U.S. Gov't
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| 700 |
1 |
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|a Hidović-Rowe, Dzena
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Pelillo, Marcello
|e verfasserin
|4 aut
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| 773 |
0 |
8 |
|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g 27(2005), 7 vom: 01. Juli, Seite 1087-99
|w (DE-627)NLM098212257
|x 1939-3539
|7 nnns
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| 773 |
1 |
8 |
|g volume:27
|g year:2005
|g number:7
|g day:01
|g month:07
|g pages:1087-99
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|a AR
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| 952 |
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|d 27
|j 2005
|e 7
|b 01
|c 07
|h 1087-99
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