2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)最新文献_第10页

Reexamining the Echo Chamber Effect of COVID-19 Vaccine Videos on YouTube 重新审视YouTube上COVID-19疫苗视频的回声室效应

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) Pub Date : 2022-11-01 DOI: 10.1109/WI-IAT55865.2022.00068

Tianlun Zhou, Paolo Mengoni

{"title":"Reexamining the Echo Chamber Effect of COVID-19 Vaccine Videos on YouTube","authors":"Tianlun Zhou, Paolo Mengoni","doi":"10.1109/WI-IAT55865.2022.00068","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00068","url":null,"abstract":"The COVID-19 pandemic has been going on for more than two years. Vaccination is believed to be one of the most efficient ways to achieve herd immunity and end pandemic. However, the contents about COVID-19 vaccines on social media have impacts on personal attitude towards vaccination. The present study aims to examine the current scenario and the echo chamber effect of COVID-19 vaccine videos on YouTube. A total of 1,646 videos with comments and replies were identified. An approach combining topic modeling, sentiment analysis, and social network analysis was employed to explore users’ attitude towards COVID-19 vaccines and whether the echo chamber effect existed. The results indicate that, even if the misleading and anti-vaccination videos were removed by the platform, \"anti-vaccination\" contents still widely appear in the comments. Moreover, the community of \"anti-vaccination\" users was more homogeneous compared with that of \"pro-vaccination\" users. The findings of this study advanced theories of echo chamber effect and the network perspective to examine echo chambers. We propose that should be paid more attention ideology echo chamber, compared with exposure echo chamber.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130963241","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

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) Pub Date : 2022-11-01 DOI: 10.1109/WI-IAT55865.2022.00055

Shuhei Kobayashi, Keishi Tajima

引用次数: 0

Family Classification of Malicious Applications using Hybrid Analysis and Computationally Economical Machine Learning Techniques 使用混合分析和计算经济机器学习技术的恶意应用程序家族分类

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) Pub Date : 2022-11-01 DOI: 10.1109/WI-IAT55865.2022.00072

P. Kishore, S. Barisal, D. Mohapatra

{"title":"Family Classification of Malicious Applications using Hybrid Analysis and Computationally Economical Machine Learning Techniques","authors":"P. Kishore, S. Barisal, D. Mohapatra","doi":"10.1109/WI-IAT55865.2022.00072","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00072","url":null,"abstract":"Most users utilize android smartphones for almost all activities. However, malicious attacks on these devices rose exponentially. Samples can be classified accurately, but earlier detection is challenging. So, we need a model that detects malicious applications before exploiting the data. This paper adopts computationally economical machine learning techniques to detect and determine the samples’ families. Applications are analyzed to create static and dynamic datasets. Five data sampling techniques are used to fix the class imbalance. After data sampling, we apply four feature selection techniques to identify the most informative features. Then, four machine learning techniques are applied to detect malware and its family. In the case of static analysis, the highest mathews correlation coefficient (MCC) is 89% for malware classification, 86% for malware category classification, and 81% for malware family classification. In the case of dynamic analysis, the highest MCC is 81% for malware category classification and 62% for malware family classification. For hybrid analysis, we achieve 88% MCC for malware category classification and 82% for malware family determination. Our proposed model outperforms other state-of-the-art performance parameters named the area under curve, accuracy, F1-measure, and MCC.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114072911","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

Adversarial Sample Generation Method for Spam SMS Classification 垃圾短信分类的对抗样本生成方法

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) Pub Date : 2022-11-01 DOI: 10.1109/WI-IAT55865.2022.00149

Ling Su, Yu Liu, Feiyan Chen, Yingqi Zhang, Haiming Zhao, Yujie Zeng

{"title":"Adversarial Sample Generation Method for Spam SMS Classification","authors":"Ling Su, Yu Liu, Feiyan Chen, Yingqi Zhang, Haiming Zhao, Yujie Zeng","doi":"10.1109/WI-IAT55865.2022.00149","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00149","url":null,"abstract":"Research shows that adding small perturbation information to the deep neural network (DNN) can lead to DNN classification errors, which is called an adversarial sample attack. Adversarial sample attack also exists in the detection of spam messages in deep neural networks. Therefore, this paper proposes an adversarial sample generation method SWordAttacker for spam messages in the black-box situation. This method designed a new calculation method of word importance, found key clauses by combining attention mechanisms, and used the scoring function to find keywords in key clauses. Finally, the adversarial samples were generated by combining attack strategies such as insertion, exchange, and similar substitution. The experiments were conducted on two DNN models, long-short memory networks(LSTM) and convolutional neural networks(CNN), using short message service(SMS) Spam datasets, and AG’s News datasets to verify the effectiveness of the proposed method. The experimental results show that SWordAttacker can greatly reduce the accuracy of the model with small perturbations and improve efficiency.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116377980","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

Organizing Search Results into a Table to Assist in Understanding and Expanding Search Target 将搜索结果组织到表格中，以帮助理解和扩展搜索目标

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) Pub Date : 2022-11-01 DOI: 10.1109/WI-IAT55865.2022.00048

Shin-ya Sato

引用次数: 0

Behavior Trees as executable representation of Milner Calculus notations 作为米尔纳演算符号的可执行表示的行为树

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) Pub Date : 2022-11-01 DOI: 10.1109/WI-IAT55865.2022.00034

Torsten Spieldenner, A. Antakli

{"title":"Behavior Trees as executable representation of Milner Calculus notations","authors":"Torsten Spieldenner, A. Antakli","doi":"10.1109/WI-IAT55865.2022.00034","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00034","url":null,"abstract":"The efforts that go into setting up stable, efficient, fault-tolerant Multi-Agent Systems are twofold: Modelling and designing agent interactions with both environment and other agents; and transfering the model into an actual executable implementation of the system. For formal modeling, notations in process calculi, such as Milner’s Calculus for Communicating Systems (CCS), have shown to be helpful, as they allow for formal model checking of the system before implementation. Typically, translating from such notations to an executable counterpart comes with pitfalls, as constraints and limitations set by the chosen programming language or software framework make a one-to-one mapping from the formal expression to executable code difficult. In this paper, we for this investigate the similarities between formal expressions in CCS, and executable behavior trees as agent programs. Our study confirms that a semantic preserving mapping between both exist, and we demonstrate how to exploit these similarities to transfer CCS expressions to semantically equivalent, executable agent programs.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115542482","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

Job Recommendation Based on Multiple Behaviors and Explicit Preferences 基于多重行为和显性偏好的工作推荐

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) Pub Date : 2022-11-01 DOI: 10.1109/WI-IAT55865.2022.00011

Yosuke Saito, Kazunari Sugiyama

{"title":"Job Recommendation Based on Multiple Behaviors and Explicit Preferences","authors":"Yosuke Saito, Kazunari Sugiyama","doi":"10.1109/WI-IAT55865.2022.00011","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00011","url":null,"abstract":"A lot of job openings have been released online, which makes job recommendation more and more important. Recently, users often enter their preferences into job search websites to receive some job recommendations that they hope to apply for. To achieve this goal, the following two types of data are available: (1) auxiliary behavior data such as viewing job postings, bookmarking them and (2) explicit preference data such as conditions for a job that each user desires. Some researchers propose job recommendation by addressing either of them. However, they have not focused on simultaneously addressing both (1) and (2) so far. Given this point, we propose a method for job recommendation that employs auxiliary behavior data and each user’s explicit preference data simultaneously. Additionally, our proposed method addresses multiple behavior overlaps and refines the latent representations. Experimental results on our dataset constructed from an actual job search website show that our proposed model outperforms several state-of-the-arts as measured by MRR and nDCG. Our source code has been released1.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130623459","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 Question Answering over Knowledge Graph of Chronic Diseases 慢性病知识图谱的问答研究

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) Pub Date : 2022-11-01 DOI: 10.1109/WI-IAT55865.2022.00088

Mengzhang Li, Haisheng Li

{"title":"Research on Question Answering over Knowledge Graph of Chronic Diseases","authors":"Mengzhang Li, Haisheng Li","doi":"10.1109/WI-IAT55865.2022.00088","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00088","url":null,"abstract":"The knowledge graph is a kind of semantic knowledge base, which can efficiently manage massive knowledge. Question answering over knowledge graph is one of the promising approaches to obtaining large information from the databases, which is applied to reply to natural language questions using structured relationship information between entities stored in knowledge graphs. Chronic disease care can be lifelong, scientific protection can have a positive effect on the recovery of patients, and lessen the incidence of complications. Therefore, this paper uses the knowledge graph to manage medical information about chronic diseases and provides users with consulting services on health issues to assist in diagnosing and treating diseases. In the paper, data is extracted from the healthcare website and stored in the graph structure database, Neo4j, after a series of data processing. We get upper and lower relationships from the data and use the extraction method, which is proved to be effective, for the domain knowledge graph construction. The platform based on high-quality knowledge, which is provided by the knowledge graph, can effectively identify user intentions and give accurate results. The research is aimed at chronic diseases and can supply references for identification, treatment, and patient self-care.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"30 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131063757","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

Personalized Video Fragment Recommendation 个性化视频片段推荐

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) Pub Date : 2022-11-01 DOI: 10.1109/WI-IAT55865.2022.00036

Jiaqi Wang, Yu-Kwong Kwok, Edith C. H. Ngai

{"title":"Personalized Video Fragment Recommendation","authors":"Jiaqi Wang, Yu-Kwong Kwok, Edith C. H. Ngai","doi":"10.1109/WI-IAT55865.2022.00036","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00036","url":null,"abstract":"In the mass market, users’ attention span over video contents is agonizingly short (e.g., 15 seconds for music/entertainment videos, 6 minutes for lecture videos, etc.), from a video producer’s or platform provider’s point of view. Given the huge amounts of existing and new videos that are significantly longer than such attention spans, a formidable research challenge is to design and implement a system for recommending just the specific fragments within a long video to match the profiles of the users.In this paper, we propose to meet this challenge based on three major insights. First, we propose to apply Self-Attention Blocks in our deep-learning framework to capture the fragment-level contextual effect. Second, we design a Video-Level Representation Module to take video-level preference into consideration when generating recommendations. Third, we propose a simple yet effective loss function for the video fragment recommendation task. Extensive experiments are conducted to evaluate the effectiveness of the proposed method. Experiment results show that our proposed framework outperforms state-of-the-art approaches in both NDCG@K and Recall@K, demonstrating judicious exploitation of fragment-level contextual effect and video-level preference. Moreover, empirical experiments are also conducted to analyze the key components and parameters in the proposed framework.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125438974","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

POWoT : a Privacy Ontology for the Web of Things poot:物联网的隐私本体

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) Pub Date : 2022-11-01 DOI: 10.1109/WI-IAT55865.2022.00026

Yacine Sam, K. Adi, Nasredine Cheniki, Noé Breton

{"title":"POWoT : a Privacy Ontology for the Web of Things","authors":"Yacine Sam, K. Adi, Nasredine Cheniki, Noé Breton","doi":"10.1109/WI-IAT55865.2022.00026","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00026","url":null,"abstract":"The W3C Web of Things (WoT) is a set of Web standards intended to enable interoperability between IoT platforms. The idea consists to propose WoT Thing Description (TD) specification that describes the metadata and interaction's interfaces of Things (IoT devices or services) at an appropriate level of abstraction based on a small vocabulary that makes it possible both to integrate diverse devices and to allow diverse applications to interoperate. TDs are made available on the network encoded in a JSON format that also allows JSON-LD processing to provide a powerful foundation to represent knowledge about Things in machine-understandable way. TD instances consist mainly of metadata about the functional part of the Thing itself, i.e., a set of interaction capabilities that indicate how the Thing can be used, possible input/output data schema, binding protocols, linking to other TD as well as the followed security schemes. Even if the latter is important to minimize some security risks in the WoT, it unfortunately does not fully take privacy aspects into consideration. We propose in this article an ontology-based privacy model to minimize privacy violation risks in the IoT context in which connected devices are increasingly able to access and manage personal data when monitoring human activities. We propose a WoT privacy ontology to enrich the TD representation with an information model allowing to specify the terms and conditions of private information management in the WoT. We then integrate this non-functional aspect in TD logic-based matchmaking and discovery process in TD Directories.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"37 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122828678","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