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Jun Peng and Baohua Su
The task of aspect-based sentiment analysis (ASBA) is to identify all the sentiment analyses expressed by specific aspect words in the text. How to identify specific objects (i.e., aspect words), describe the modifiers of the specific objects (i.e., opin...
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Hao Liu, Bo Yang and Zhiwen Yu
Multimodal sarcasm detection is a developing research field in social Internet of Things, which is the foundation of artificial intelligence and human psychology research. Sarcastic comments issued on social media often imply people?s real attitudes towa...
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Mahammad Khalid Shaik Vadla, Mahima Agumbe Suresh and Vimal K. Viswanathan
Understanding customer emotions and preferences is paramount for success in the dynamic product design landscape. This paper presents a study to develop a prediction pipeline to detect the aspect and perform sentiment analysis on review data. The pre-tra...
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Xiu Li, Aron Henriksson, Martin Duneld, Jalal Nouri and Yongchao Wu
Educational content recommendation is a cornerstone of AI-enhanced learning. In particular, to facilitate navigating the diverse learning resources available on learning platforms, methods are needed for automatically linking learning materials, e.g., in...
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Achintya Kumar Sarkar and Zheng-Hua Tan
Deep representation learning has gained significant momentum in advancing text-dependent speaker verification (TD-SV) systems. When designing deep neural networks (DNN) for extracting bottleneck (BN) features, the key considerations include training targ...
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Benjamin Shade and Eduardo G. Altmann
Quantifying the dissimilarity of two texts is an important aspect of a number of natural language processing tasks, including semantic information retrieval, topic classification, and document clustering. In this paper, we compared the properties and per...
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Zhen Sun and Xinfu Li
Named entity recognition can deeply explore semantic features and enhance the ability of vector representation of text data. This paper proposes a named entity recognition method based on multi-head attention to aim at the problem of fuzzy lexical bounda...
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Iwona Kaczmarek, Adam Iwaniak and Aleksandra Swietlicka
Classification is one of the most-common machine learning tasks. In the field of GIS, deep-neural-network-based classification algorithms are mainly used in the field of remote sensing, for example for image classification. In the case of spatial data in...
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Rui Zhang, Chengrong Xue, Qingfu Qi, Liyuan Lin, Jing Zhang and Lun Zhang
The enrichment of social media expression makes multimodal sentiment analysis a research hotspot. However, modality heterogeneity brings great difficulties to effective cross-modal fusion, especially the modality alignment problem and the uncontrolled ve...
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Pingshan Liu, Qi Liang and Zhangjing Cai
Aiming at addressing the inability of traditional web technologies to effectively respond to Winter-Olympics-related user questions containing multiple intentions, this paper explores a multi-model fusion-based multi-intention recognition model BCNBLMATT...
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