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Multimodal Machine Translation
2021
IEEE Access
Preserved Fulltext
Therefore, two attention mechanisms are simultaneously used to capture text and image contexts for translation. ...
As the scale of data is getting larger and larger and deep neural network models are widely used, pre-training technology has been widely used and has achieved remarkable results, but it has also received ...
Chen for their help in this work. ...
doi:10.1109/access.2021.3115135
fatcat:d2anaeg3qnarpfmlc4eap2urrm
Deep Learning, Natural Language Processing, and Explainable Artificial Intelligence in the Biomedical Domain
[article]
2022
arXiv
pre-print
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Deep learning methods are then described in Section 2. ...
Deep learning neural networks explained in this section have been widely used to implement powerful NLP systems for a wide variety of applications such as Information retrieval, named entity recognition ...
In this example, a bi-RNN is used for the encoder and a forward RNN is used for the decoder. ...
arXiv:2202.12678v2
fatcat:4nv42mbpuveb7euxkr4b6ojuxi
A Unified Approach of Detecting Misleading Images via Tracing its Instances on Web and Analysing its Past Context for the Verification of Content
[article]
2021
arXiv
pre-print
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It also demonstrates the efficiency of our proposed approach and features using both Machine and Deep Learning Model (Bi-directional LSTM). ...
In this paper, we investigated machine learning-based as well as deep learning-based approaches utilized to verify misleading multimedia content, where the available image traces are used to identify the ...
an image via tracing it on an image search engine and then collecting its past instances to retrieve the relevant crucial knowledge for prediction using both deep and machine learning models. Prominently ...
arXiv:2109.09929v1
fatcat:6sv3tv4o4jfsjjkh5aolxle3eu
Brain Informatics
2011
IEEE Intelligent Systems
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New kinds of BI methods and global research communities will emerge to develop a platform on the intelligent Web and knowledge grids that enable high-speed, distributed, large-scale analysis and computations ...
and radically B rain informatics (BI) is an emerging interdisciplinary and multidisciplinary research fi eld that focuses on studying the mechanisms underlying the human information processing system ...
Three Aspects of Brain Informatics Studies Three aspects of BI studies deserve closer attention: systematic investigations for complex brain science problems, new information technologies for supporting ...
doi:10.1109/mis.2011.83
fatcat:rewrtcysqjdgjdjfhbybtd6w3a
A Survey on Incorporating Domain Knowledge into Deep Learning for Medical Image Analysis
[article]
2020
arXiv
pre-print
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2020 pre-print arXiv:2004.12150v2 fatcat:j2hrsapa5jejhef2u3lhmedrbeOther Versions
In this survey, we summarize the current progress on integrating medical domain knowledge into deep learning models for various tasks, such as disease diagnosis, lesion, organ and abnormality detection ...
they pay particular attention to. ...
A dual-attention model is designed to facilitate the high-level interaction of semantic information and visual information. ...
arXiv:2004.12150v3
fatcat:2cqumcjkizgivmo67reznxacie
Hierarchical Network Emotional Assistance Mechanism for Emotion Cause Extraction
2022
Security and Communication Networks
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This method uses a hierarchical network composed of bidirectional gated recurrent units, attention mechanism, and graph convolutional networks to capture clause context information, deep semantic information ...
Thus, a model of the deep neural network combined with the emotional assistance mechanism is established. ...
Different weight matrices are used for context propagation according to different edges. ...
doi:10.1155/2022/3597771
fatcat:rq4emposbve2lfpro325yva2za
Fine-Grained Chemical Entity Typing with Multimodal Knowledge Representation
[article]
2021
arXiv
pre-print
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Automated knowledge discovery from trending chemical literature is essential for more efficient biomedical research. ...
cross-modal attention to learn effective representation of text in the chemistry domain. ...
of incorporating non-local features, which may have added additional useful information for entity type disambiguation. ...
arXiv:2108.12899v1
fatcat:cib35n544vdo5pj34ztrm7jowy
DeepAnalyze: Learning to Localize Crashes at Scale
[article]
2021
arXiv
pre-print
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These insights enable us to develop DeepAnalyze, a novel multi-task sequence labeling approach for identifying blamed frames in stack traces. ...
The analysis provides valuable insights on where and how the crashes happen and what methods to blame for the crashes. ...
To the best of our knowledge, DeepAnalyze is the first effort to use MTL in context of debugging. ...
arXiv:2109.14326v2
fatcat:47g3c3hlwrbv7mellrsefltfse
Recent Trends in Deep Learning Based Open-Domain Textual Question Answering Systems
2020
IEEE Access
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Open-domain textual question answering (QA), which aims to answer questions from large data sources like Wikipedia or the web, has gained wide attention in recent years. ...
INDEX TERMS Open-domain textual question answering, deep learning, machine reading comprehension, information retrieval. ...
BiDAF [87] and Multi-Perspective Matching [95] leveraged Bi-LSTM for semantic information aggregation. ...
doi:10.1109/access.2020.2988903
fatcat:po4euxfronf3pob52qc2wcgrre
Evolution of Semantic Similarity – A Survey
[article]
2021
arXiv
pre-print
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2020 pre-print arXiv:2004.13820v1 fatcat:3o6bk23u7zh2zd7oc4y722zzbu
This survey article traces the evolution of such methods, categorizing them based on their underlying principles as knowledge-based, corpus-based, deep neural network-based methods, and hybrid methods. ...
The versatility of natural language makes it difficult to define rule-based methods for determining semantic similarity measures. ...
and Andrew Heppner for their feedback and revisions on this publication. ...
arXiv:2004.13820v2
fatcat:fh7jkq7cyvczdnxarhscya2u4u
A Survey on Deep Learning Based Point-Of-Interest (POI) Recommendations
[article]
2020
arXiv
pre-print
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To the best of our knowledge, this work is the first comprehensive survey of all major deep learning-based POI recommendation works. ...
for a user. ...
[77] uses an attention mechanism designed for utilizing spatiotemporal information. ...
arXiv:2011.10187v1
fatcat:3uampnqerfdvnpuzrxcrsjviwq
Unbox the Blackbox: Predict and Interpret YouTube Viewership Using Deep Learning
[article]
2022
arXiv
pre-print
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2021 pre-print arXiv:2101.01076v3 fatcat:ulk5afk2rbgmxbhozqre4y3z5uOther Versions
Following the design-science paradigm, we propose a novel interpretable IT system, Precise Wide and Deep Learning (PrecWD), to precisely interpret viewership prediction. ...
Predicting video viewership is a top priority for content creators and video-sharing sites. Content creators live on such predictions to maximize influences and minimize budgets. ...
Perceived usefulness, ease of use, and usage of information technology: A replication. MIS quarterly. 1992 Jun 1:227-47. ...
arXiv:2101.01076v5
fatcat:wzbxm32ndvespfnlgngawqfkyq
SoftNER: Mining Knowledge Graphs From Cloud Incidents
[article]
2021
arXiv
pre-print
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First, we build a novel multi-task learning based BiLSTM-CRF model which leverages not just the semantic context but also the data-types for extracting factual information in the form of named entities ...
Lastly, using the knowledge extracted by SoftNER, we are able to build accurate models for applications such as incident triaging and recommending entities based on their relevance to incident titles. ...
We leverage syntactic pattern extractors for bootstrapping the training data. Further, we incorporate a novel multi-task BiLSTM-CRF deep learning model with an attention mechanism. ...
arXiv:2101.05961v2
fatcat:envypijvyvej3lieo3yqudf6ri
Machine Reading Comprehension: The Role of Contextualized Language Models and Beyond
[article]
2020
arXiv
pre-print
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With the burst of deep neural networks and the evolution of contextualized language models (CLMs), the research of MRC has experienced two significant breakthroughs. ...
We depict the simple but widely-used matching attention M in Figure 8 -(b) for example, whose formulation is further described in §5.6.3 for detailed reference. ...
Knowledge Injection. Extra knowledge can be easily incorporated into CLMs by both embedding fusion and masking. ...
arXiv:2005.06249v1
fatcat:htdq7hk6mrghvknwbkchgdioku
Knowledgeable Reader: Enhancing Cloze-Style Reading Comprehension with External Commonsense Knowledge
[article]
2018
arXiv
pre-print
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Instead of relying only on document-to-question interaction or discrete features as in prior work, our model attends to relevant external knowledge and combines this knowledge with the context representation ...
By including knowledge explicitly, our model can also provide evidence about the background knowledge used in the RC process. ...
We thank the reviewers for their helpful questions and comments. ...
arXiv:1805.07858v1
fatcat:ta2ii3sxafhgnmvhoonubo2lt4
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