The amount of textual information available electronically has made it difficult for many users to find and access the right information within acceptable time. Research communities in the natural language processing (NLP) field are developing tools and techniques to alleviate these problems and help users in exploiting these vast resources. These techniques include Information Retrieval (IR) a...

This paper describes experiments to establish the performance of a named entity recognition system which builds categorized lists of names from manually annotated training data. Names in text are then identi ed using only these lists. This approach does not perform as well as state-of-the-art named entity recognition systems. However, we then show that by using simple ltering techniques for imp...

The amount of textual information available electronically has made it difficult for many users to find and access the right information within acceptable time. Research communities in the natural language processing (NLP) field are developing tools and techniques to alleviate these problems and help users in exploiting these vast resources. These techniques include Information Retrieval (IR) a...

Personal name recognition is an important part of named entity recognition in Web search query logs. An unsupervised method for Chinese personal name recognition in queries is proposed using search session. Based on seed personal names which are produced automatically by introducing Chinese surnames, a local expansion method is proposed by using search sessions in query logs;and by modeling the...

We present a hybrid NER (Name Entity Recognition) system for Urdu script by integration of n-gram model (unigram and bigram), rules and gazetteers. We used prefix and suffix characters for rule construction instead of first name and last name lists or potential terms on the output list that is produced by n-gram model. Evaluation of the system is performed on two corpora, the IJCNLP NE (Named E...

In order to build an automatic named entity recognition (NER) system for machine learning, a large tagged corpus is necessary. This paper describes the manual construction of a Chinese named entity tagged corpus (CNEC 1.0) that can be used to improve NER performance. In this project, we define five named entity tags: PER (person name), LOC (location name), ORG (organization name), LAO (location...

Recognition of Chinese location entity is an important part of event extraction. In this paper we propose a novel method to identify Chinese location entity based on the divide-and-conquer strategy. Firstly, we use CRF role labeling to identify the basic place name. Secondly, by using semi-automatic way, we build indicator lexicon. Finally, we propose attachment connection algorithm to connect ...

In the analysis of natural language text a key step is named entity recognition, finding all complex noun phrases that denote persons, organizations, locations, and other entities designated by a name. In this paper we introduce the hunner open source language-independent named entity recognition system, and present results for Hungarian. When the input to hunner is already morphologically anal...

Entity recognition is an important but challenging research problem. In reality, many text collections are from specific, dynamic, or emerging domains, which poses significant new challenges for entity recognition with increase in name ambiguity and context sparsity, requiring entity detection without domain restriction. In this paper, we investigate entity recognition (ER) with distant-supervi...

Complex networks can be used to describe the Internet, social network, or more broadly describe a binary relation of a set of objects. Structure information of complex network helps the identification of the entity corresponding to nodes in the network. There is much research in this area, and the authors introduce these studies and their results in this chapter. The authors mainly present two ...