Title: Language Identification as Process Prediction Using WoMan
Abstract: Several high-level tasks in the management of Digital Libraries require the application of Natural Language Processing (NLP) techniques. In turn, most NLP solutions are based on linguistic resources that are costly to produce, and so motivate research for automated ways to build them. In particular, Language Identification is a crucial NLP task, that is preliminary to almost all the others, since different linguistic resources must be used for different languages. This paper investigates process mining and management approaches as a possible solution to the Language Identification problem. Specifically, it casts language identification as a process prediction task, and exploits the WoMan framework to carry it out. Experimental results are encouraging and suggest to further explore this approach.
Publication Year: 2017
Publication Date: 2017-01-01
Language: en
Type: book-chapter
Indexed In: ['crossref']
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Cited By Count: 3
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