Titlebook: Computational Linguistics and Intelligent Text Processing; 15th International C Alexander Gelbukh Conference proceedings 2014 Springer-Verl

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The Hong Kong Polytechnic Universityr understanding of text and helps to significantly increase the accuracy of many text mining tasks. Concept extraction from text is a key step in concept-level text analysis. In this paper, we propose a ConceptNet-based semantic parser that deconstructs natural language text into concepts based on t

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https://doi.org/10.1007/978-3-319-46034-5s learning methods only utilize homo-lingual corpus. Inspired by transfer learning, we propose a novel language transfer method to obtain word embeddings via language transfer. Under this method, in order to obtain word embeddings of one language (target language), we train models on corpus of anoth

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Metamorphosis

Student Engagement in Neoliberal Timesrd may present different signatures in different contexts, i.e. polysemous words can be used with different senses in different contexts. Intuitively, disambiguating word senses for topic models can enhance their discriminative capabilities. In this work, we propose a joint model to automatically in

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杀人

https://doi.org/10.1007/978-981-10-3200-4for morphological segmentation from a computational linguistics point of view. We survey morphological segmentation methods covering methods based on MDL (minimum description length), MLE (maximum likelihood estimation), MAP (maximum a posteriori), parametric and non-parametric Bayesian approaches.

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Towards a Critical Curriculum for Engagementn from developers. One of such under-resourced languages is Kafi-noonoo which is spoken in the south-western regions of Ethiopia. This paper presents the development of part-of-speech tagger for Kafi-noonoo. In order to develop the tagger, we employed a hybrid of two systems: statistical and rule-ba