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Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology最新文献

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Improving Topic Modeling Performance through N-gram Removal 通过N-gram去除提高主题建模性能
Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Pub Date : 2021-12-14 DOI: 10.1145/3486622.3493952
Mohamad Almgerbi, Andrea De Mauro, Adham Kahlawi, V. Poggioni
{"title":"Improving Topic Modeling Performance through N-gram Removal","authors":"Mohamad Almgerbi, Andrea De Mauro, Adham Kahlawi, V. Poggioni","doi":"10.1145/3486622.3493952","DOIUrl":"https://doi.org/10.1145/3486622.3493952","url":null,"abstract":"In recent years, topic modeling has been increasingly adopted for finding conceptual patterns in large corpora of digital documents to organize them accordingly. In order to enhance the performance of topic modeling algorithms, such as Latent Dirichlet Allocation (LDA), multiple preprocessing steps have been proposed. In this paper, we introduce N-gram Removal, a novel preprocessing procedure based on the systematic elimination of a dynamic number of repeated words in text documents. We have evaluated the effects of the utilization of N-gram Removal through four different performance metrics: we concluded that its application is effective at improving the performance of LDA and enhances the human interpretation of topics models.","PeriodicalId":89230,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"109 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81062335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Consumer research based on the consumption of IP virtual derivatives 基于IP虚拟衍生品消费的消费者研究
Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Pub Date : 2021-12-14 DOI: 10.1145/3498851.3498949
Yuhan Gu, Zhenbiao He
{"title":"Consumer research based on the consumption of IP virtual derivatives","authors":"Yuhan Gu, Zhenbiao He","doi":"10.1145/3498851.3498949","DOIUrl":"https://doi.org/10.1145/3498851.3498949","url":null,"abstract":"In the context of industrial development, IP can be understood as \"copyright\", i.e., ownership of cultural products with a wide audience base and commercial exploitation value. IP virtual derivatives are a special form of IP derivatives in the midstream of the IP licensing and development industry chain. Users and consumers in the downstream of IP virtual derivatives industry chain are one of the most important parts of the industry chain, and industry development needs to understand users' preferences and needs in order to develop more special and irreplaceable products in the competitive market, harvest users' attention and traffic, and finally complete product realization.","PeriodicalId":89230,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"67 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80100402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Session details: Chapter 10: WImBI21: Web Intelligence meets Brain Informatics 会议细节:第10章:WImBI21:网络智能与脑信息学
Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Pub Date : 2021-12-14 DOI: 10.1145/3530283
{"title":"Session details: Chapter 10: WImBI21: Web Intelligence meets Brain Informatics","authors":"","doi":"10.1145/3530283","DOIUrl":"https://doi.org/10.1145/3530283","url":null,"abstract":"","PeriodicalId":89230,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"87 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80143683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
EEG Spatial Analysis based on Brain thermogram Image Recognition 基于脑热成像图像识别的脑电空间分析
Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Pub Date : 2021-12-14 DOI: 10.1145/3498851.3498951
Mingzhen Ding, Ziyi Liu, Guohui Xu, Shudong Ding, Hao Lan Zhang
{"title":"EEG Spatial Analysis based on Brain thermogram Image Recognition","authors":"Mingzhen Ding, Ziyi Liu, Guohui Xu, Shudong Ding, Hao Lan Zhang","doi":"10.1145/3498851.3498951","DOIUrl":"https://doi.org/10.1145/3498851.3498951","url":null,"abstract":"EEG feature recognition is an important research issue for understanding human brain activities. However, the invasive solution for brain informatics research is causing concerns on its safety and reliability. Therefore, current research in brain informatics field pays more attention on non-invasive brain analysis. In this paper, we introduce a novel solution, which combines EEG signal analysis with EEG heat spots image recognition based on the Convolutional Neural Network (CNN) method. The experimental results demonstrate our solution can enhance the EEG feature recognition.","PeriodicalId":89230,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"56 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79742394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Modular Design Patterns for Systems that Learn and Reason 学习和推理系统的模块化设计模式
Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Pub Date : 2021-12-14 DOI: 10.1145/3486622.0000004
F. V. Harmelen
{"title":"Modular Design Patterns for Systems that Learn and Reason","authors":"F. V. Harmelen","doi":"10.1145/3486622.0000004","DOIUrl":"https://doi.org/10.1145/3486622.0000004","url":null,"abstract":"The combination of data-driven techniques from machine learning with symbolic techniques from knowledge representation is recognised as one of the grand challenges of modern AI. We propose a set of compositional design patterns to describe a large variety of systems that combine statistical techniques from machine learning with symbolic techniques from knowledge representation. As in other areas of computer science (knowledge engineering, software engineering, ontology engineering, process mining and others), such design patterns help to systematize the literature, clarify which combinations of techniques serve which purposes, and encourage re-use of software components. We have validated our set of compositional design patterns against a large body of recent literature.","PeriodicalId":89230,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78126360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Semantic Segmentation of Atherosclerosis in Superficial Layer of IVOCT Images Using Deep Learning 基于深度学习的IVOCT图像浅层动脉粥样硬化语义分割
Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Pub Date : 2021-12-14 DOI: 10.1145/3498851.3498953
X. Ren, Haiyuan Wu, Toshiyuki Imai, Yuxia Zhao, T. Kubo
{"title":"Semantic Segmentation of Atherosclerosis in Superficial Layer of IVOCT Images Using Deep Learning","authors":"X. Ren, Haiyuan Wu, Toshiyuki Imai, Yuxia Zhao, T. Kubo","doi":"10.1145/3498851.3498953","DOIUrl":"https://doi.org/10.1145/3498851.3498953","url":null,"abstract":"Labeling the lesion tissue pixel-by-pixel is a serious process for cardiovascular disease (CAD) doctors, which causes time-consuming and low effectiveness. We proposed an automatic method with deep learning technology to classify the vessel tissue on the intravascular optical coherence tomography (IVOCT) image with a pixel level. Considering that only the superficial layer contains valuable information about the tissue, we firstly segmented the region of interest (ROI) by using the level set method and cropped square patches from it as the input data of neural network for the purpose of utilizing the analyzable area and increasing the data volume to improve the generalization of the network model. We chose SegNet to implement the learning procedure and predicted the classification of each pixel of cropped patches. Finally, constructing a 3-D volume to place each prediction on each slice and finding out the maximum type number of every pixel as the final class of lesion tissue. The classification results show that Our method presents a considerable approach as a computer-assisted tool for doctors.","PeriodicalId":89230,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"56 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82357835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Enhance while protecting: privacy preserving image filtering 增强的同时保护:隐私保护图像过滤
Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Pub Date : 2021-12-14 DOI: 10.1145/3486622.3493999
Diego Arcelli, Alina Elena Baia, A. Milani, V. Poggioni
{"title":"Enhance while protecting: privacy preserving image filtering","authors":"Diego Arcelli, Alina Elena Baia, A. Milani, V. Poggioni","doi":"10.1145/3486622.3493999","DOIUrl":"https://doi.org/10.1145/3486622.3493999","url":null,"abstract":"Privacy is an important issue raised from the diffusion of deep learning models. These models are able to extract unauthorized information from our data, especially from the images shared on Social Networks. In this work we present a nested evolutionary algorithm able to optimize sequences of Instagram-style image filters that, when applied to an image, are able to protect it by fooling classification systems: we turn adversarial attacks into a defence form. Differently from other adversarial techniques adding small perturbations that cannot be easily detected by human eyes but can be easily recognized by softwares, our filter composition cannot be distinguished from any other filter composition used extensively every day to enhance photos and images.","PeriodicalId":89230,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"37 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73027156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Dual-Channel Domain Adaptation Model 双通道域适应模型
Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Pub Date : 2021-12-14 DOI: 10.1145/3498851.3498984
Chi Yang, Bo Zhou, Xiaohui Hu, Jianying Chen, Qianhua Cai, Yun Xue
{"title":"Dual-Channel Domain Adaptation Model","authors":"Chi Yang, Bo Zhou, Xiaohui Hu, Jianying Chen, Qianhua Cai, Yun Xue","doi":"10.1145/3498851.3498984","DOIUrl":"https://doi.org/10.1145/3498851.3498984","url":null,"abstract":"Document-level cross-domain sentiment analysis aims to leverage useful information in the source domain to help infer document-level sentiment on the target domain. The existing cross-domain sentiment analysis methods neglect complex syntactic structure and diversified semantic information of document text in different domains. Therefore, we proposed a novel dual-channel domain adaptation model (DCDA) for document-level cross-domain sentiment analysis. It consists of feature extraction module and domain adaptation module. The dual-channel feature extraction module adopts hierarchical attention structure to extract context channel features at word level and sentence level. In addition, different attention strategies are implemented at different levels, which enables accurate assigning of the attention weight. GAT is used to extract syntactic channel characteristics of documents. We adopt adversarial mutual learning in the domain adaptation module. It learns the domain-invariant features by using adversarial network learning, and makes full use of the information of the target domain to improve the classification effect by mutual learning. Experiments on multiple public datasets demonstrate the effectiveness of DCDA.","PeriodicalId":89230,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"333 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77630313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Playbour in the Digital Games:A Case Study of Fantasy Westward Journey 数字游戏中的游戏性:以《梦幻西游》为例
Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Pub Date : 2021-12-14 DOI: 10.1145/3498851.3498954
Jing Bao
{"title":"Playbour in the Digital Games:A Case Study of Fantasy Westward Journey","authors":"Jing Bao","doi":"10.1145/3498851.3498954","DOIUrl":"https://doi.org/10.1145/3498851.3498954","url":null,"abstract":"The problem of playbour in digital games has always been a key research field of the political economy of communication. The following issues are widely disputed: the productivity of playbour, the exploitation and monitoring of playbour, and the initiative of palybour. This article expolres the playbour problem in the game world by conducting a digital ethnographic investigation of the online game “ Fantasy Westward Journey”.","PeriodicalId":89230,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73995525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Towards Better Evidence Extraction Methods for Fact-Checking Systems 为事实核查系统提供更好的证据提取方法
Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Pub Date : 2021-12-14 DOI: 10.1145/3486622.3493930
Pedro Azevedo, Gil Rocha, Diego Esteves, Henrique Lopes Cardoso
{"title":"Towards Better Evidence Extraction Methods for Fact-Checking Systems","authors":"Pedro Azevedo, Gil Rocha, Diego Esteves, Henrique Lopes Cardoso","doi":"10.1145/3486622.3493930","DOIUrl":"https://doi.org/10.1145/3486622.3493930","url":null,"abstract":"Given current levels of misinformation spread, never before have fact-checking frameworks been so critical. Unfortunately, the performance of Automated Fact-checking systems is still poor due to the complexity of the task. In this paper, we present an ablation study of a framework submitted to the FEVER 1.0 challenge. Based on our findings, we explore how triple-based information retrieval, coreference resolution, and recent language model representations can impact the performance of each subtask. We show the importance of recall and precision in the retrieval of documents and sentences that can be provided to justify the veracity of a given claim. We reach state-of-the-art results in the Document Retrieval task and we show promising results when using coreference resolution to improve the Sentence Retrieval task.","PeriodicalId":89230,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"62 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74643157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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