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Automatic text tagging is an important component in higher level analysis of text corpora, and its output can be used in many natural language processing applica- tions. In languages like …...

Noun extraction is very important for many NLP applications such as informa- tion retrieval, automatic text classification, and information extraction. Most of the previous Korean noun extraction systems use a …...

We introduce a new, linguistically grounded measure of collocativity based on the property of limited modifiability and test it on German PP-verb combinations. We show that our mea- sure not …...

We investigate the problem of learn- ing a part-of-speech (POS) lexicon for a resource-poor language, dialectal Arabic. Developing a high-quality lexicon is often the first step towards building a POS …...

AbstractApplications of statistical Arabic NLP in general, and text mining in specific, along with the tools underneath perform much better as the statistical processing operates on deeper language factorization(s) than …...

Zulu is an indigenous language of South Africa, and one of the eleven official languages of that country. It is spoken by about 11 million speakers. Although it is similar …...

AbstractIn this paper we present AnIta, a powerful morphological analyser for Italian implemented within the framework of finite-state-automata models. It is provided by a large lexicon containing more than 110,000 …...

AbstractDomain adaptation is an important task in order for NLP systems to work well in real applications. There has been extensive research on this topic. In this paper, we address …...

We present a simple, yet effective approach to adapt part-of-speech (POS) taggers to new domains. Our approach only requires a dic- tionary and large amounts of unlabeled tar- get data. …...

AbstractHistorical texts are challenging for natural language processing because they differ linguistically from modern texts and because of their lack of orthographical and grammatical standardisation. We use a character-level neural …...

AbstractBecause of the small size of Romanian corpora, the performance of a PoS tagger or a dependency parser trained with the standard supervised methods fall far short from the performance …...

In this paper we present our system de- veloped for the SemEval 2016 Task 2 - Interpretable Semantic Textual Similarity along with the results obtained for our sub- mitted runs. …...

AbstractWe present a simple but effective method for aspect identification in sentiment analysis. Our unsupervised method only requires word embeddings and a POS tagger, and is therefore straightforward to apply …...