Named Entity Recognition for Nepali Text Using Support Vector Machines

Named Entity Recognition with Support Vector Machines

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. The completed system was trained to recognize Named E...

Named Entity Recognition in Persian Text using Deep Learning

Named entities recognition is a fundamental task in the field of natural language processing. It is also known as a subset of information extraction. The process of recognizing named entities aims at finding proper nouns in the text and classifying them into predetermined classes such as names of people, organizations, and places. In this paper, we propose a named entity recognizer which benefi...

Tuning support vector machines for biomedical named entity recognition

We explore the use of Support Vector Machines (SVMs) for biomedical named entity recognition. To make the SVM training with the available largest corpus – the GENIA corpus – tractable, we propose to split the non-entity class into sub-classes, using part-of-speech information. In addition, we explore new features such as word cache and the states of an HMM trained by unsupervised learning. Expe...

Use of Support Vector Machines in Extended Named Entity Recognition

Use of Support Vector Machines in Extended Named Entity Recognition

This paper explores the use of Support Vector Machines (SVMs) for an extended named entity task. We investigate the identification and classification of technical terms in the molecular biology domain and contrast this to results obtained for traditional NE recognition on the MUC-6 data set. Furthermore we compare the performance of the SVM model to a standard HMM bigram model. Results show tha...