[PDF] Top 20 Global Model for Hierarchical Multi Label Text Classification
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Global Model for Hierarchical Multi Label Text Classification
... Exploring features that capture other types of inter-label dependencies is a good research direc- tion. For example, “Others” labels probably be- have atypically in relation to their siblings. While we focus on ... See full document
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HMC-ReliefF: Feature Ranking for Hierarchical Multi-label Classification
... Abstract. In machine learning, the growing complexity of the available data poses an increased challenge for its analysis. The rising complexity is both in terms of the data becoming more high-dimensional as well as the ... See full document
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Learning Hierarchical Multi Category Text Classification Models
... the classification framework, review loss functions and derive a quadratic optimization prob- lem for finding the maximum margin model param- ...and hierarchical SVM learning approaches and the ... See full document
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Multi Task Label Embedding for Text Classification
... proposed Multi-Task Label Embedding (MTLE) to map labels of each task into semantic vectors, similar to how Word Em- bedding deals with word sequences, thereby turn- ing the original tasks into vector ... See full document
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Latent Dirichlet Allocation complement in the vector space model for Multi Label Text Classification
... the multi-label context we would like to mention some, which are closer related to our ...Semantic Model, when words or stems are grouped into clusters based on their semantic ... See full document
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Extreme Multi Label Legal Text Classification: A Case Study in EU Legislation
... MIMIC - III , it had exceptional results in few-shot and zero-shot learning, being able to identify la- bels with few or no instances at all in the train- ing sets. Experimental results showed an improve- ment of ... See full document
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Extension of TSVM to Multi Class and Hierarchical Text Classification Problems With General Losses
... each label over the labeled and unlabeled ...for multi-class and structured output ...direct multi-class and hierarchical classification formulation in ... See full document
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Label Specific Document Representation for Multi Label Text Classification
... each label can be taken as one aspect or component of the document, thus, the overall semantics of the whole document can be formed by multiple ...novel Label-Specific Attention Network model (LSAN) ... See full document
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Leveraging Hierarchical Category Knowledge for Data Imbalanced Multi Label Diagnostic Text Understanding
... the hierarchical learning with aver- age ...CNN model, and the best perfor- mance comes from the one with multi-task learn- ...that multi-task learn- ing has more flexible constraints compared ... See full document
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Development of Rule-Based Feature Extraction in Multi-label Text Classification
... the classification method, where a multi-label binary relevance approach was used to change the multi-label classification into a binary classification, because the simple ... See full document
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Unsupervised multi-label text classification using a world knowledge ontology
... in text classification is ...build classification models, which is similar as the strategy employed in our ...pattern-based classification al- gorithm using short ...a text ... See full document
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SGM: Sequence Generation Model for Multi label Classification
... Multi-label classification is an important yet challenging task in natural language ...single-label classification in that the labels tend to be ...the text can contribute ... See full document
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A Deep Reinforced Sequence to Set Model for Multi Label Classification
... to model label correlations by leveraging ...both global and local semantic ...Seq2Seq model to capture the label ...convolution model and Zhao et al. (2018) present a ... See full document
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Large Scale Multi Label Text Classification on EU Legislation
... HAN : The Hierarchical Attention Network (Yang et al., 2016) is a strong baseline for text classification. We use a slightly modified version, where a BIGRU with self-attention reads the words of ... See full document
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Semantic Unit Based Dilated Convolution for Multi Label Text Classification
... our model with fewer parameters still outperforms the hierarchical model with the deterministic setting of sentence or ...different hierarchical models with different boundaries, which sets ... See full document
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Hierarchical Text Classification with Latent Concepts
... The global approach builds only one classifier to discriminate all categories in a hierarchy(Cai and Hofmann, 2004; Rousu et ...of global approach is that the close classes have some com- mon underlying ... See full document
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Hierarchical Transfer Learning for Multi label Text Classification
... of multi-label text classification re- search has been exploiting possible label depen- dencies to improve predictive ...for label dependencies, some approaches utilize ... See full document
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Hierarchical Text Classification with Reinforced Label Assignment
... Although global methods are de- sirable, they are relatively less studied due to the complexity of the ...Existing global mod- els are generally modified based on specific flat ...models. ... See full document
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Hierarchical Multi label Classification of Text with Capsule Networks
... In hierarchical multi-label classification (HMC), samples are classified into one or multiple class labels that are organized in a structured label hier- archy (Silla and Freitas, ... See full document
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Initializing neural networks for hierarchical multi label text classification
... for multi-label classification lies in leverag- ing the co-occurrence between ...for hierarchical multi-label classification, because of the implicit hypernym–hyponym ... See full document
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