Paper Info
Title
Using Semantics in Matching Cursive Chinese Handwritten Annotations
Abstract
We propose a semantic matching network for the matching of cursive Chinese handwritten annotations. This architecture combines the semantics of Chinese language with the traditional elastic ink matching. Using semantics can make the matching algorithm more intelligent by pre-selecting the most likely candidates before elastic ink matching is applied thus speed up the whole matching process. The semantic matching network can also establish a link between Chinese handwritten annotations and typed text, which can be used to match between these two. Our experiments show that 75 – 85% recall can be achieved with a speed improvement of 85% over traditional elastic ink matching.
Year
DOI
Venue
1998
10.1007/BFb0033247
SSPR/SPR
Field
DocType
ISBN
Edit distance,Cursive,Pattern recognition,Computer science,Pattern analysis,Handwriting recognition,Artificial intelligence,Natural language processing,Semantics,Blossom algorithm,Speedup,Semantic matching
Conference
3-540-64858-5
Citations 
PageRank 
References 
1
0.38
10
Authors
2
Name
Order
Citations
PageRank
Matthew Y. Ma1807.97
patrick s p wang230347.66