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Hittade 5 uppsatser som matchar ovanstående sökkriterier.
1. Cross-Lingual and Genre-Supervised Parsing and Tagging for Low-Resource Spoken Data
Master-uppsats, Uppsala universitet/Institutionen för lingvistik och filologiSammanfattning : Dealing with low-resource languages is a challenging task, because of the absence of sufficient data to train machine-learning models to make predictions on these languages. One way to deal with this problem is to use data from higher-resource languages, which enables the transfer of learning from these languages to the low-resource target ones. LÄS MER
2. Natural Language Processing Model for Maltese Syntax
Magister-uppsats, Göteborgs universitet/Institutionen för filosofi, lingvistik och vetenskapsteoriSammanfattning : The objective of this thesis is to create a Natural Language Processing Model for the Maltese Language. The ultimate goal is that the model would be able to recognise syntactical features, that is the linguistic features and the relationship of a sequence of words, in Maltese. LÄS MER
3. Neural Networks for Part-of-Speech Tagging
Kandidat-uppsats, Linköpings universitet/Institutionen för datavetenskapSammanfattning : The aim of this thesis is to explore the viability of artificial neural networks using a purely contextual word representation as a solution for part-of-speech tagging. Furthermore, the effects of deep learning and increased contextual information of the network are explored. LÄS MER
4. Genetic Algorithms in the Brill Tagger : Moving towards language independence
Magister-uppsats, Avdelningen för datorlingvistikSammanfattning : The viability of using rule-based systems for part-of-speech tagging was revitalised when a simple rule-based tagger was presented by Brill (1992). This tagger is based on an algorithm which automatically derives transformation rules from a corpus, using an error-driven approach. LÄS MER
5. Named Entity Recognition with Support Vector Machines
Master-uppsats, KTH/Skolan för datavetenskap och kommunikation (CSC)Sammanfattning : This report describes a degree project in Computer Science, the aim of which was to construct a system for Named Entity Recognition in Swedish texts of names of people, locations and organizations, as well as expressions for time. This system was constructed from the part-of-speech tagger Granska and the Support Vector Machine system SVMlin. LÄS MER