Relation extraction with weakly supervised learning based on process-structure-property-performance reciprocity
نویسندگان
چکیده
منابع مشابه
Deep Residual Learning for Weakly-Supervised Relation Extraction
Deep residual learning (ResNet) (He et al., 2016) is a new method for training very deep neural networks using identity mapping for shortcut connections. ResNet has won the ImageNet ILSVRC 2015 classification task, and achieved state-of-theart performances in many computer vision tasks. However, the effect of residual learning on noisy natural language processing tasks is still not well underst...
متن کاملMulti-Task Transfer Learning for Weakly-Supervised Relation Extraction
Creating labeled training data for relation extraction is expensive. In this paper, we study relation extraction in a special weakly-supervised setting when we have only a few seed instances of the target relation type we want to extract but we also have a large amount of labeled instances of other relation types. Observing that different relation types can share certain common structures, we p...
متن کاملWeakly-supervised Relation Extraction by Pattern-enhanced Embedding Learning
Extracting relations from text corpora is an important task in text mining. It becomes particularly challenging when focusing on weakly-supervised relation extraction, that is, utilizing a few relation instances (i.e., a pair of entities and their relation) as seeds to extract more instances from corpora. Existing distributional approaches leverage the corpus-level co-occurrence statistics of e...
متن کاملA Weakly-Supervised Rule-Based Approach for Relation Extraction
Resumen Rule-based approaches for information extraction usually achieve good precision values, even if they often need a lot of manual effort to be implemented. In this paper, we present a novel rule-based strategy for semantic relation extraction that takes advantage of partial syntactic parsing in order to simplify the linguistic structures containing instances of semantic relations. We also...
متن کاملSemantic Relation Extraction Based on Semi-supervised Learning
Many tasks of information extraction or natural language processing have a property that the data naturally consist of several views—disjoint subsets of features. Specifically, a semantic relationship can be represented with some entity pairs or contexts surrounding the entity pairs. For example, the PersonBirthplace relation can be recognized from the entity pair view, such as (Albert Einstein...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Science and Technology of Advanced Materials
سال: 2018
ISSN: 1468-6996,1878-5514
DOI: 10.1080/14686996.2018.1500852