Semi-Supervised Bootstrapping Approach for Named Entity Recognition
نویسندگان
چکیده
منابع مشابه
Semi-supervised Bootstrapping approach for Named Entity Recognition
The aim of Named Entity Recognition (NER) is to identify references of named entities in unstructured documents, and to classify them into pre-defined semantic categories. NER often aids from added background knowledge in the form of gazetteers. However using such a collection does not deal with name variants and cannot resolve ambiguities associated in identifying the entities in context and a...
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We present ASemiNER, a semisupervised algorithm for identifying Named Entities (NEs) in Arabic text. ASemiNER does not require annotated training data, or gazetteers. It also can be easily adapted to handle more than the three standard NE types (Person, Location, and Organisation). To our knowledge, our algorithm is the first study that intensively investigates the semi-supervised pattern-based...
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We present a simple semi-supervised learning algorithm for named entity recognition (NER) using conditional random fields (CRFs). The algorithm is based on exploiting evidence that is independent from the features used for a classifier, which provides high-precision labels to unlabeled data. Such independent evidence is used to automatically extract highaccuracy and non-redundant data, leading ...
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Bootstrapping is the process of improving the performance of a trained classifier by iteratively adding data that is labeled by the classifier itself to the training set, and retraining the classifier. It is often used in situations where labeled training data is scarce but unlabeled data is abundant. In this paper, we consider the problem of domain adaptation: the situation where training data...
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We propose a general cross-domain bootstrapping algorithm for domain adaptation in the task of named entity recognition. We first generalize the lexical features of the source domain model with word clusters generated from a joint corpus. We then select target domain instances based on multiple criteria during the bootstrapping process. Without using annotated data from the target domain and wi...
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ژورنال
عنوان ژورنال: International Journal on Natural Language Computing
سال: 2015
ISSN: 2319-4111,2278-1307
DOI: 10.5121/ijnlc.2015.4501