Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology最新文献_第3页

The Unified Authority Platform based on High Performance Blockchain 基于高性能区块链的统一授权平台

Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Pub Date : 2021-12-14 DOI: 10.1145/3498851.3498923

Guanqun Yang, Q. Ma, Meng Liu, Qiang Zhangiu, Hao Xu, Xiaolu Chen

{"title":"The Unified Authority Platform based on High Performance Blockchain","authors":"Guanqun Yang, Q. Ma, Meng Liu, Qiang Zhangiu, Hao Xu, Xiaolu Chen","doi":"10.1145/3498851.3498923","DOIUrl":"https://doi.org/10.1145/3498851.3498923","url":null,"abstract":"Along with the popularization of enterprise management information system (MIS), more and more business application systems are integrated on the MIS platform, and the need for user identity and authentication management is increasing quickly, which puts forward higher requirements for the security, reliability and disaster recovery of the unified identity authentication service of the unified authority platform. Therefore, there is an urgent need for a new technology architecture to meet the business management needs of unified identity authentication and continuously improve the operation guarantee ability of information communication. Blockchain technology has developed rapidly and has been successfully applied in many fields, especially in data security, with good results. This paper proposes a unified authority authentication mechanism for complex systems based on blockchain, and realizes accurate authority management by dynamically defining user roles, accessible resources and access methods. At the same time, data compression storage technology and parallel access method are used to realize rapid access to blockchain permissions, and improve access efficiency on the premise of ensuring security. Experiments show that the proposed method can realize the dynamic unified control of complex permissions. Compared with ordinary blockchain systems, it has higher access efficiency, and the average authentication time is reduced by more than 39%.","PeriodicalId":89230,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"93 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80249043","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

HRS: Hybrid Recommendation System based on Attention Mechanism and Knowledge Graph Embedding 基于注意机制和知识图嵌入的混合推荐系统

Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Pub Date : 2021-12-14 DOI: 10.1145/3498851.3498987

Chunfang Dong, Xuchan Ju, Yue Ma

引用次数: 2

Disease Classification on Admission and on Discharge with Residual CNN-Transformer 有线电视变压器残留的入院和出院疾病分类

Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Pub Date : 2021-12-14 DOI: 10.1145/3486622.3493946

Yu-Ting Lin, Sheng-Lun Wei, Hen-Hsen Huang, Hui-Chih Wang, Hsin-Hsi Chen

{"title":"Disease Classification on Admission and on Discharge with Residual CNN-Transformer","authors":"Yu-Ting Lin, Sheng-Lun Wei, Hen-Hsen Huang, Hui-Chih Wang, Hsin-Hsi Chen","doi":"10.1145/3486622.3493946","DOIUrl":"https://doi.org/10.1145/3486622.3493946","url":null,"abstract":"Clinical professionals perform disease classification on both admission and discharge of a patient, but previous works ignore the former. Physicians make a preliminary diagnosis based solely on current observations such as chief complaint and present illness at the admission time. Only limited information is available to decide which examination or treatment to make afterward. On discharge, complete medical records during hospitalization are available for deciding the International Classification of Diseases (ICD) code. Either occasion should be covered in a comprehensive disease classification system to meet the reality. Besides, from the technical perspective, previous state-of-the-art models employ the per-label attention mechanism to aggregate the contextualized vectors, less capable of handling the multi-label classification task up to 8,921 codes. In this paper, we conduct a comprehensive study on disease classification on both the admission and the discharge of patients. Furthermore, we propose a novel multi-head label decoding method that can replace the per-label attention module adopted by previous works. Experimental results show that our model achieves state-of-the-art performance in both admission and discharge scenarios.","PeriodicalId":89230,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82431205","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

Research on A Machine Scoring Method of Role-Play Section in English Oral Test 英语口语考试角色扮演部分机器评分方法研究

Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Pub Date : 2021-12-14 DOI: 10.1145/3498851.3498983

Xinguang Li, Zhihe Yang, Shuai Chen, Shanxian Ma

{"title":"Research on A Machine Scoring Method of Role-Play Section in English Oral Test","authors":"Xinguang Li, Zhihe Yang, Shuai Chen, Shanxian Ma","doi":"10.1145/3498851.3498983","DOIUrl":"https://doi.org/10.1145/3498851.3498983","url":null,"abstract":"Computer-assisted instruction has been widely implemented in language learning since the remarkable development of speech technology and natural language processing. In English teaching, the traditional manual evaluation mode has been replaced by the computer. In this paper, we introduce a machine scoring method of Role-Play Section in the English oral test. Specifically, we design a scoring method of Role-Play section in Computer-based English Listening and Speaking Test (CELST) of the Guangdong college entrance examination (GDCEE), which can simulate human scoring. The role-play section is also called Three Questions (TQ) and Five Answers (FA), so two scoring modules are established, respectively. According to the features of the role-play section and the given manual scoring scale, the scoring task can be regarded as a short text similarity evaluation task, and we propose a corresponding multi-index text similarity evaluation method. Statistic-based word matching and keyword-focused semantic similarity evaluations are adopted in the TQ and FA scoring modules. Additionally, we consider the grammar factor and utilize semantic similarity-combined dependency parsing evaluation for TQ scoring. Based on the above five evaluative indicators, we linearly integrate them and corresponding expertise-based weights with linear regression optimization, thus constructing a comprehensive scoring model of the role-play Section in CELST. Experiments were conducted using real oral data of examinees in GDCEE. Results have indicated that the machine scoring method achieves impressive data consistency with human scoring.","PeriodicalId":89230,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81068249","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

Fine-Tuning for Cross-Domain Aspect-Based Sentiment Classification 跨领域基于方面的情感分类的微调

Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Pub Date : 2021-12-14 DOI: 10.1145/3486622.3494003

S. V. Berkum, Sophia van Megen, Max Savelkoul, Pim Weterman, F. Frasincar

{"title":"Fine-Tuning for Cross-Domain Aspect-Based Sentiment Classification","authors":"S. V. Berkum, Sophia van Megen, Max Savelkoul, Pim Weterman, F. Frasincar","doi":"10.1145/3486622.3494003","DOIUrl":"https://doi.org/10.1145/3486622.3494003","url":null,"abstract":"Aspect-Based Sentiment Classification (ABSC) is a subfield of sentiment analysis concerned with classifying sentiment attributed to pre-identified aspects. A problem in ABSC nowadays is the limited availability of labeled data for certain domains. This study aims to improve sentiment classification accuracy for these domains where labeled data is scarce. Our proposed approach is to apply cross-domain fine-tuning to a state-of-the-art deep learning method designed for ABSC: LCR-Rot-hop++. For this purpose, we initially train the model on a domain that has a lot of labeled data available and consecutively fine-tune the upper layers with training data of the target domain. The performance of the fine-tuning method is evaluated relative to a model that is trained from scratch for each target domain. For the initial training, restaurant review data is used. For the fine-tuning and from-scratch training we use review data for laptops, books, hotels, and electronics. Our results show that when comparing the fine-tuning with the from-scratch method (for the same training set), the fine-tuning method on average outperforms the from-scratch method when the training set is small for all considered domains and is considerably faster.","PeriodicalId":89230,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89339950","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: 5

Research on Clustering Protocol in Mobile Ad Hoc Networks 移动Ad Hoc网络中的聚类协议研究

Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Pub Date : 2021-12-14 DOI: 10.1145/3498851.3499000

Zhijie Han, Wei-hua Xue, Xiaoyu Du

{"title":"Research on Clustering Protocol in Mobile Ad Hoc Networks","authors":"Zhijie Han, Wei-hua Xue, Xiaoyu Du","doi":"10.1145/3498851.3499000","DOIUrl":"https://doi.org/10.1145/3498851.3499000","url":null,"abstract":"Mobile ad hoc network (MANET), composing of wireless nodes with communication functions, is an autonomous network system which is temporary, multi-hop and centerless. Its installation does not require any infrastructure, and can be widely used in military, emergency and disaster relief, harsh natural environment and inconvenient transportation. Nodes in MANET use wireless transceivers to send and receive signals between nodes. Nodes send data to cluster heads and then forward them uniformly. Due to the limited energy of nodes, communication between nodes should effectively use energy to extend the network life cycle. This paper is based on this background, aiming at the clustering problem of MANET. Before clustering, the elbow method is combined with the silhouette coefficient, and the similarity in the cluster and the dissimilarity between the clusters are introduced to avoid the local optimal solution. Finally, the clustering algorithm is used to cluster the nodes. In the selection of cluster head, the ring model is used to optimize the selection of cluster head by comprehensively considering the residual energy of nodes and the distance between nodes and the cluster center. It effectively prolongs the network lifetime of mobile ad hoc networks, improves the network throughput and reduces the packet loss rate.","PeriodicalId":89230,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86711629","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: 2

CADPP: An Effective Approach to Recommend Attentive and Diverse Long-tail Items CADPP:一种有效的长尾项目推荐方法

Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Pub Date : 2021-12-14 DOI: 10.1145/3486622.3493961

Shuai Tang, Xiaofeng Zhang

{"title":"CADPP: An Effective Approach to Recommend Attentive and Diverse Long-tail Items","authors":"Shuai Tang, Xiaofeng Zhang","doi":"10.1145/3486622.3493961","DOIUrl":"https://doi.org/10.1145/3486622.3493961","url":null,"abstract":"As the long-tail items are widely seen in various recommendation related applications, e.g., E-commerce and music recommendation, the long-tail recommendation consequently becomes an important research issue attracting both academic and industrial attentions. Apparently, it is a very challenging practical issue and the corresponding key challenges to address this task is to find the long-tail items which best match users’ preferences but are sufficiently diverse to avoid recommending similar long-tail items. To address this issue, this paper proposes a novel long-tail item recommendation approach which is based on the multi-pointer co-attention mechanism and the determinant point process (abbreviated as CADPP). Specifically, we design the multi-pointer co-attention mechanism for extracting important feature embeddings to capture the common characteristics of multiple items clicked by the users. We also employ the determinant point process (DPP) to allow diverse long-tail items but are relevant to the target items. To evaluate the model performance, extensive experiments have been performed on two real-world datasets. The promising results have demonstrated that the proposed CADPP is superior to both baseline and the state-of-the-art approaches with respect to the widely adopted evaluation metrics.","PeriodicalId":89230,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"65 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83950790","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

VOISMA: Indoor Location Identification for Voice-based Smart Home VOISMA:基于语音的智能家居室内位置识别

Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Pub Date : 2021-12-14 DOI: 10.1145/3486622.3493995

Mahda Noura, M. Gaedke

引用次数: 0

Research on online medical community doctor recommendation based on information fusion 基于信息融合的在线医疗社区医生推荐研究

Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Pub Date : 2021-12-14 DOI: 10.1145/3498851.3499008

Zhiqiang Gu, Yuejin Zhang

引用次数: 1

Heterogeneous Graph Learning for Explainable Recommendation over Academic Networks 异构图学习在学术网络上的可解释推荐

Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Pub Date : 2021-12-14 DOI: 10.1145/3498851.3498926

Xiangtai Chen, Tao Tang, Jing Ren, Ivan Lee, Honglong Chen, Feng Xia

{"title":"Heterogeneous Graph Learning for Explainable Recommendation over Academic Networks","authors":"Xiangtai Chen, Tao Tang, Jing Ren, Ivan Lee, Honglong Chen, Feng Xia","doi":"10.1145/3498851.3498926","DOIUrl":"https://doi.org/10.1145/3498851.3498926","url":null,"abstract":"With the explosive growth of new graduates with research degrees every year, unprecedented challenges arise for early-career researchers to find a job at a suitable institution. This study aims to understand the behavior of academic job transition and hence recommend suitable institutions for PhD graduates. Specifically, we design a deep learning model to predict the career move of early-career researchers and provide suggestions. The design is built on top of scholarly/academic networks, which contains abundant information about scientific collaboration among scholars and institutions. We construct a heterogeneous scholarly network to facilitate the exploring of the behavior of career moves and the recommendation of institutions for scholars. We devise an unsupervised learning model called HAI (Heterogeneous graph Attention InfoMax) which aggregates attention mechanism and mutual information for institution recommendation. Moreover, we propose scholar attention and meta-path attention to discover the hidden relationships between several meta-paths. With these mechanisms, HAI provides ordered recommendations with explainability. We evaluate HAI upon a real-world dataset against baseline methods. Experimental results verify the effectiveness and efficiency of our approach.","PeriodicalId":89230,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87328676","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: 3