Comparing Data-Driven Learning Algorithms for PoS Tagging of Swedish

Data-Driven Methods for PoS Tagging and Chunking of Swedish

An improved joint model: POS tagging and dependency parsing

Dependency parsing is a way of syntactic parsing and a natural language that automatically analyzes the dependency structure of sentences, and the input for each sentence creates a dependency graph. Part-Of-Speech (POS) tagging is a prerequisite for dependency parsing. Generally, dependency parsers do the POS tagging task along with dependency parsing in a pipeline mode. Unfortunately, in pipel...

Recent Advances in Memory-Based Part-of-Speech Tagging

Memory based learning algorithms are lazy learners Examples of a task are stored in memory and processing is largely postponed to the time when new instances of the task need to be solved This is then done by extrapolating directly from those remem bered instances which are most similar to the present ones Using memory based learning for Part of Speech tagging has a number of advantages over tr...

Learning from Within? Comparing PoS Tagging Approaches for Historical Text

In this paper, we investigate unsupervised and semi-supervised methods for part-of-speech (PoS) tagging in the context of historical German text. We locate our research in the context of Digital Humanities where the non-canonical nature of text causes issues facing an Natural Language Processing world in which tools are mainly trained on standard data. Data deviating from the norm requires tool...

سیستم برچسب گذاری اجزای واژگانی کلام در زبان فارسی

Abstract: Part-Of-Speech (POS) tagging is essential work for many models and methods in other areas in natural language processing such as machine translation, spell checker, text-to-speech, automatic speech recognition, etc. So far, high accurate POS taggers have been created in many languages. In this paper, we focus on POS tagging in the Persian language. Because of problems in Persian POS t...