Textual information is becoming available in abundance on the web, arising the requirement
of techniques and tools to extract the meaningful information. One of such an important …

As more and more Arabic texts emerged on the Internet, extracting important information
from these Arabic texts is especially useful. As a fundamental technology, Named entity …

Abstract We present CAMeL Tools, a collection of open-source tools for Arabic natural
language processing in Python. CAMeL Tools currently provides utilities for pre-processing …

As more and more Arabic textual information becomes available through the Web in homes
and businesses, via Internet and Intranet services, there is an urgent need for technologies …

Named entity recognition (NER) is the problem of locating and categorizing important nouns
and proper nouns in a text. In this chapter, we review the general state of research on entity …

Storytelling, and the delivery of societal narratives, enable human beings to communicate,
connect, and understand one another and the world around them. Narratives can be defined …

In this paper, we propose a hybrid named entity recognition (NER) approach that takes the
advantages of rule-based and machine learning-based approaches in order to improve the …

Most of the Arabic Named Entity Recognition (NER) systems depend massively on external
resources and handmade feature engineering to achieve state-of-the-art results. To …

ABSTRACT Most Arabic Named Entity Recognition (NER) systems have been developed
using either of two approaches: a rule-based or Machine Learning (ML) based approach …

矿产资源地质报告中蕴含大量专家经验及基础地质知识. 快速准确地从海量矿产资源文本中抽取
形成结构化知识已成为目前研究热点, 命名实体识别是信息抽取与知识挖掘的重要步骤 …