[PDF] Top 20 Label Embedding using Hierarchical Structure of Labels for Twitter Classification
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Label Embedding using Hierarchical Structure of Labels for Twitter Classification
... a hierarchical struc- ture, which is regarded as important informa- ...tion. Label texts of pre-defined classes them- selves also include important clues for clas- ...the hierarchical ... See full document
6
Hierarchical Multi label Classification of Text with Capsule Networks
... (2018) show that capsule networks can outperform traditional neural networks for TC by a great mar- gin when training on single-labeled and testing on multi-labeled documents of the Reuters-21578 dataset since the ... See full document
8
NeuralClassifier: An Open source Neural Hierarchical Multi label Text Classification Toolkit
... cific classification tasks, including binary-class, multi-class, multi-label and ...multi-class) classification task, we provide three candidate loss functions, which are SoftmaxCrossEntopy, BCLoss ... See full document
6
Hierarchical deep neural networks for MeSH subject prediction
... the labels themselves and trains to predict labels based solely on their independent relevance to each ...of label independence is violated in real-world applications, which often exhibit a ... See full document
44
Learning Sentiment Specific Word Embedding for Twitter Sentiment Classification
... feature set of NRC leaving out ngram features. Except for DistSuper, other baseline method- s are conducted in a supervised manner. We do not compare with RNTN (Socher et al., 2013b) be- cause we cannot efficiently train ... See full document
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Hierarchical Transfer Learning for Multi label Text Classification
... HTrans (Hierarchical Transfer Learning) is based on a recursive strategy of training parent and child category classifiers. Say, P1 is a top-level category with C1 as one of its children. Also, lets consider C12 ... See full document
6
Global Model for Hierarchical Multi Label Text Classification
... in hierarchical multi- label text classification is how to leverage hierarchically organized ...multiple labels to be output, which has been left unused in previous ...tiple labels and ... See full document
9
Joint Embedding of Hierarchical Categories and Entities for Concept Categorization and Dataless Classification
... Dataless classification uses the similarity between documents and labels in an enriched semantic space to determine in which category the given document ...dataless classification (Song and Roth, ... See full document
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Initializing neural networks for hierarchical multi label text classification
... defined labels to input text, where the la- bels are a part of a hierarchical structure (such as a ...(OVR) classification setup, where a binary clas- sifier is trained for each label ... See full document
9
Hierarchical ensemble classification: towards the classification of data collections that feature large numbers of class labels
... of hierarchical ensemble classification approaches are proposed as a solution to the multi-class classification ...tive classification can be produced if a “coarse-grain” classification ... See full document
293
Multi Task Label Embedding for Text Classification
... 2016a) introduce an external memory for informa- tion sharing with a reading/writing mechanism for communications. (Liu et al., 2016b) propose three different models for MTL with RNN and (Zhang et al., 2017) constructs a ... See full document
9
Hierarchical Text Classification with Reinforced Label Assignment
... models. Hierarchical-SVM (Cai and Hofmann, 2004; Qiu et ...the label hierarchy. One limitation is that Hierarchical-SVM only supports balanced tree (all possible labels are presumed to be at ... See full document
11
Joint Embedding of Words and Labels for Text Classification
... sentiment classification (Zhou et ...including hierarchical attention networks (Yang et ...joint embedding space of words and labels, and the context is specified by the label ... See full document
11
Deep contextualized word representations for detecting sarcasm and irony
... Apart from the relevance for industry applications related to sentiment analysis, sarcasm and irony detection has received great traction within the NLP research community, resulting in a variety of methods, shared tasks ... See full document
6
Distributional Semantics Meets Multi-Label Learning
... The this paper we establish a connection between word2vec in NLP with multi-label learning in XML. The benefit leap by the connection is efficient and fast training, easy handling of the missing label ... See full document
8
Comparative Study of Various Sentiment Classification Techniques in Twitter
... as Twitter, Tumblr, ...mine Twitter for information about what user think about their services and ...products. Twitter contains a very large number of short ...poll twitter for analysing or ... See full document
9
Indexing discrete sets in a label setting algorithm for solving the elementary shortest path problem with resource constraints
... The Elementary Shortest Path Problem with Resource Con- straints (ESPPRC) is a combinatorial optimization problem where given a graph the goal is to find a set of least cost paths that satisfy constraints expressed as ... See full document
8
HMC-ReliefF: Feature Ranking for Hierarchical Multi-label Classification
... The directions for further work regarding our HMC-ReliefF algorithm are numer- ous. One major direction would be to define an artificial, controlled setting for investi- gating HMC problems in the context of feature ... See full document
24
Modeling Composite Labels for Neural Morphological Tagging
... morphological labels has occurred in the context of morphological disambiguation—a task where the goal is to select the correct analy- sis from a limited set of candidates provided by a morphological ...complex ... See full document
12
Twitter Polarity Classification with Label Propagation over Lexical Links and the Follower Graph
... Full sentiment analysis for a given question or topic requires many stages, including but not lim- ited to: (1) extraction of tweets based on an ini- tial query, (2) filtering out spam and irrelevant items from those ... See full document
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