
doi: 10.1007/bfb0033261
We consider the problem of grammatical inference (GI) for classes of structured documents like summaries, dictionaries, bibliographic data basis, encyclopaedias and so on. The inference is based on examples of individual sample of these documents. In this paper, we present an algebraic framework of the GI in which rewrite rules will define the process of generalisation. The implementation algorithm discussed here is used in a document handling project in which paper documents are typographically tagged and then recognised. One of the current applications in this project is to translate paper documents into machine readable form
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL], [INFO] Computer Science [cs]
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL], [INFO] Computer Science [cs]
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
