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- research-articleNovember 2022
Multi-Label Annotation and Classification of Arabic Texts Based on Extracted Seed Keyphrases and Bi-Gram Alphabet Feed Forward Neural Networks Model
ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), Volume 22, Issue 1Article No.: 31, Pages 1–16https://doi.org/10.1145/3539607In natural language processing, text classification is a fundamental problem. Multi-label classification of textual data is a challenging topic in text classification where an instance can be associated with more than one label. This paper presents a ...
- research-articleJuly 2021
Generic Multi-label Annotation via Adaptive Graph and Marginalized Augmentation
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 16, Issue 1Article No.: 12, Pages 1–20https://doi.org/10.1145/3451884Multi-label learning recovers multiple labels from a single instance. It is a more challenging task compared with single-label manner. Most multi-label learning approaches need large-scale well-labeled samples to achieve high accurate performance. However,...
- posterNovember 2014
Exploring Shared Subspace and Joint Sparsity for Canonical Correlation Analysis
CIKM '14: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge ManagementPages 1887–1890https://doi.org/10.1145/2661829.2661970Canonical correlation analysis (CCA) has been extensively employed in various real-world applications of multi-label annotation. However, two major challenges are raised by the classical CCA. First, CCA frequently fails to remove noisy and irrelevant ...
- research-articleJune 2012
Labelset anchored subspace ensemble (LASE) for multi-label annotation
ICMR '12: Proceedings of the 2nd ACM International Conference on Multimedia RetrievalArticle No.: 42, Pages 1–8https://doi.org/10.1145/2324796.2324846In multimedia retrieval, multi-label annotation for image, text and video is challenging and attracts rapidly growing interests in past decades. The main crux of multi-label annotation lies on 1) how to reduce the model complexity when the label space ...
- research-articleOctober 2010
Multi-label boosting for image annotation by structural grouping sparsity
MM '10: Proceedings of the 18th ACM international conference on MultimediaPages 15–24https://doi.org/10.1145/1873951.1873957We can obtain high-dimensional heterogenous features from real-world images to describe their various aspects of visual characteristics, such as color, texture and shape etc.Different kinds of heterogenous features have different intrinsic ...
- articleSeptember 2010
DO WE AGREE? MEASURING AGREEMENT ON THE HUMAN JUDGMENTS IN EMOTION ANNOTATION OF NEWS SENTENCES
Cybernetics and Systems (CSYS), Volume 41, Issue 7Pages 469–488https://doi.org/10.1080/01969722.2010.511525An emotional text may be judged to belong to multiple emotion categories because it may evoke different emotions with varying degrees of intensity. For emotion analysis of text in a supervised manner, it is required to annotate text corpus with emotion ...
