首页 > 最新文献

Journal of Intelligent Information Systems最新文献

英文 中文
MMusic: a hierarchical multi-information fusion method for deep music recommendation MMusic:一种分层多信息融合的深度音乐推荐方法
IF 3.4 3区 计算机科学 Q2 Computer Science
Journal of Intelligent Information Systems
Pub Date : 2023-06-29 DOI: 10.1007/s10844-023-00786-0
Jing Xu, Mingxin Gan, Xiongtao Zhang
{"title":"MMusic: a hierarchical multi-information fusion method for deep music recommendation","authors":"Jing Xu, Mingxin Gan, Xiongtao Zhang","doi":"10.1007/s10844-023-00786-0","DOIUrl":"https://doi.org/10.1007/s10844-023-00786-0","url":null,"abstract":"","PeriodicalId":56119,"journal":{"name":"Journal of Intelligent Information Systems","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85387073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Audio-based anomaly detection on edge devices via self-supervision and spectral analysis 基于自监督和频谱分析的边缘设备音频异常检测
IF 3.4 3区 计算机科学 Q2 Computer Science
Journal of Intelligent Information Systems
Pub Date : 2023-06-28 DOI: 10.1007/s10844-023-00792-2
Fabrizio Lo Scudo, E. Ritacco, Luciano Caroprese, G. Manco
{"title":"Audio-based anomaly detection on edge devices via self-supervision and spectral analysis","authors":"Fabrizio Lo Scudo, E. Ritacco, Luciano Caroprese, G. Manco","doi":"10.1007/s10844-023-00792-2","DOIUrl":"https://doi.org/10.1007/s10844-023-00792-2","url":null,"abstract":"","PeriodicalId":56119,"journal":{"name":"Journal of Intelligent Information Systems","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73653795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
TuckerDNCaching: high-quality negative sampling with tucker decomposition TuckerDNCaching:带tucker分解的高质量负采样
IF 3.4 3区 计算机科学 Q2 Computer Science
Journal of Intelligent Information Systems
Pub Date : 2023-06-20 DOI: 10.1007/s10844-023-00796-y
Tiroshan Madushanka, R. Ichise
{"title":"TuckerDNCaching: high-quality negative sampling with tucker decomposition","authors":"Tiroshan Madushanka, R. Ichise","doi":"10.1007/s10844-023-00796-y","DOIUrl":"https://doi.org/10.1007/s10844-023-00796-y","url":null,"abstract":"","PeriodicalId":56119,"journal":{"name":"Journal of Intelligent Information Systems","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74710233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Information gain based dynamic support set construction for cold-start recommendation 基于信息增益的冷启动推荐动态支持集构建
IF 3.4 3区 计算机科学 Q2 Computer Science
Journal of Intelligent Information Systems
Pub Date : 2023-06-16 DOI: 10.1007/s10844-023-00795-z
Yu Li, T. Furukawa
{"title":"Information gain based dynamic support set construction for cold-start recommendation","authors":"Yu Li, T. Furukawa","doi":"10.1007/s10844-023-00795-z","DOIUrl":"https://doi.org/10.1007/s10844-023-00795-z","url":null,"abstract":"","PeriodicalId":56119,"journal":{"name":"Journal of Intelligent Information Systems","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89870307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
SMGNN: span-to-span multi-channel graph neural network for aspect-sentiment triplet extraction SMGNN:面向方面-情感三元组抽取的跨到跨多通道图神经网络
IF 3.4 3区 计算机科学 Q2 Computer Science
Journal of Intelligent Information Systems
Pub Date : 2023-06-13 DOI: 10.1007/s10844-023-00794-0
Barakat AlBadani, Jian Dong, Ronghua Shi, Raeed Al-Sabri, Dhekra Saeed, Alaa Thobhani
{"title":"SMGNN: span-to-span multi-channel graph neural network for aspect-sentiment triplet extraction","authors":"Barakat AlBadani, Jian Dong, Ronghua Shi, Raeed Al-Sabri, Dhekra Saeed, Alaa Thobhani","doi":"10.1007/s10844-023-00794-0","DOIUrl":"https://doi.org/10.1007/s10844-023-00794-0","url":null,"abstract":"","PeriodicalId":56119,"journal":{"name":"Journal of Intelligent Information Systems","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73438853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Identifying multimodal misinformation leveraging novelty detection and emotion recognition. 利用新颖性检测和情绪识别识别多模式错误信息。
IF 3.4 3区 计算机科学 Q2 Computer Science
Journal of Intelligent Information Systems
Pub Date : 2023-06-06 DOI: 10.1007/s10844-023-00789-x
Rina Kumari, Nischal Ashok, Pawan Kumar Agrawal, Tirthankar Ghosal, Asif Ekbal

With the growing presence of multimodal content on the web, a specific category of fake news is rampant on popular social media outlets. In this category of fake online information, real multimedia contents (images, videos) are used in different but related contexts with manipulated texts to mislead the readers. The presence of seemingly non-manipulated multimedia content reinforces the belief in the associated fabricated textual content. Detecting this category of misleading multimedia fake news is almost impossible without relevance to any prior knowledge. In addition to this, the presence of highly novel and emotion-invoking contents can fuel the rapid dissemination of such fake news. To counter this problem, in this paper, we first introduce a novel multimodal fake news dataset that includes background knowledge (from authenticate sources) of the misleading articles. Second, we design a multimodal framework using Supervised Contrastive Learning (SCL) based novelty detection and Emotion Prediction tasks for fake news detection. We perform extensive experiments to reveal that our proposed model outperforms the state-of-the-art (SOTA) models.

随着网络上多模式内容的日益增多，一类特定的假新闻在流行的社交媒体上泛滥。在这类虚假网络信息中，真实的多媒体内容（图像、视频）被用于不同但相关的上下文中，并被操纵文本以误导读者。看似未被操纵的多媒体内容的存在强化了人们对相关捏造文本内容的信念。如果没有任何先验知识，几乎不可能检测出这类误导性的多媒体假新闻。除此之外，高度新颖和情绪化的内容的出现会助长此类假新闻的快速传播。为了解决这个问题，在本文中，我们首先介绍了一个新的多模式假新闻数据集，该数据集包括误导性文章的背景知识（来自认证来源）。其次，我们使用基于监督对比学习（SCL）的新颖性检测和情绪预测任务设计了一个用于假新闻检测的多模式框架。我们进行了大量的实验，以表明我们提出的模型优于最先进的（SOTA）模型。
{"title":"Identifying multimodal misinformation leveraging novelty detection and emotion recognition.","authors":"Rina Kumari,&nbsp;Nischal Ashok,&nbsp;Pawan Kumar Agrawal,&nbsp;Tirthankar Ghosal,&nbsp;Asif Ekbal","doi":"10.1007/s10844-023-00789-x","DOIUrl":"10.1007/s10844-023-00789-x","url":null,"abstract":"<p><p>With the growing presence of multimodal content on the web, a specific category of fake news is rampant on popular social media outlets. In this category of fake online information, real multimedia contents (images, videos) are used in different but related contexts with manipulated texts to mislead the readers. The presence of seemingly non-manipulated multimedia content reinforces the belief in the associated fabricated textual content. Detecting this category of misleading multimedia fake news is almost impossible without relevance to any prior knowledge. In addition to this, the presence of <i>highly novel</i> and <i>emotion-invoking</i> contents can fuel the rapid dissemination of such fake news. To counter this problem, in this paper, we first introduce a novel multimodal fake news dataset that includes <i>background knowledge</i> (from authenticate sources) of the misleading articles. Second, we design a multimodal framework using <i>Supervised Contrastive Learning (SCL) based novelty detection</i> and <i>Emotion Prediction</i> tasks for fake news detection. We perform extensive experiments to reveal that our proposed model outperforms the state-of-the-art (SOTA) models.</p>","PeriodicalId":56119,"journal":{"name":"Journal of Intelligent Information Systems","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10242597/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9720385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
A semiautomatic method for obtaining a predictive deep learning model and a rule-based system for abdominal aortic aneurysms 一种获得预测深度学习模型的半自动方法和基于规则的腹主动脉瘤系统
IF 3.4 3区 计算机科学 Q2 Computer Science
Journal of Intelligent Information Systems
Pub Date : 2023-06-05 DOI: 10.1007/s10844-023-00781-5
Alberto Nogales, Fernando Gallardo, Miguel Pajares, Javier Martinez Gamez, José Moreno, Á. García-Tejedor
{"title":"A semiautomatic method for obtaining a predictive deep learning model and a rule-based system for abdominal aortic aneurysms","authors":"Alberto Nogales, Fernando Gallardo, Miguel Pajares, Javier Martinez Gamez, José Moreno, Á. García-Tejedor","doi":"10.1007/s10844-023-00781-5","DOIUrl":"https://doi.org/10.1007/s10844-023-00781-5","url":null,"abstract":"","PeriodicalId":56119,"journal":{"name":"Journal of Intelligent Information Systems","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82706706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A novel approach for software defect prediction using CNN and GRU based on SMOTE Tomek method 一种基于SMOTE Tomek方法的基于CNN和GRU的软件缺陷预测新方法
IF 3.4 3区 计算机科学 Q2 Computer Science
Journal of Intelligent Information Systems
Pub Date : 2023-05-16 DOI: 10.1007/s10844-023-00793-1
N. A. A. Khleel, K. Nehéz
{"title":"A novel approach for software defect prediction using CNN and GRU based on SMOTE Tomek method","authors":"N. A. A. Khleel, K. Nehéz","doi":"10.1007/s10844-023-00793-1","DOIUrl":"https://doi.org/10.1007/s10844-023-00793-1","url":null,"abstract":"","PeriodicalId":56119,"journal":{"name":"Journal of Intelligent Information Systems","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72388850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
BERT-PG: a two-branch associative feature gated filtering network for aspect sentiment classification 面向方面情感分类的双分支关联特征门控过滤网络
IF 3.4 3区 计算机科学 Q2 Computer Science
Journal of Intelligent Information Systems
Pub Date : 2023-05-16 DOI: 10.1007/s10844-023-00785-1
Jiamei Wang, Wei Wu, Jiansi Ren
{"title":"BERT-PG: a two-branch associative feature gated filtering network for aspect sentiment classification","authors":"Jiamei Wang, Wei Wu, Jiansi Ren","doi":"10.1007/s10844-023-00785-1","DOIUrl":"https://doi.org/10.1007/s10844-023-00785-1","url":null,"abstract":"","PeriodicalId":56119,"journal":{"name":"Journal of Intelligent Information Systems","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89881849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Multilingual deep learning framework for fake news detection using capsule neural network. 使用胶囊神经网络检测假新闻的多语言深度学习框架。
IF 2.3 3区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal of Intelligent Information Systems
Pub Date : 2023-05-09 DOI: 10.1007/s10844-023-00788-y
Rami Mohawesh, Sumbal Maqsood, Qutaibah Althebyan

Fake news detection is an essential task; however, the complexity of several languages makes fake news detection challenging. It requires drawing many conclusions about the numerous people involved to comprehend the logic behind some fake stories. Existing works cannot collect more semantic and contextual characteristics from documents in a particular multilingual text corpus. To bridge these challenges and deal with multilingual fake news detection, we present a semantic approach to the identification of fake news based on relational variables like sentiment, entities, or facts that may be directly derived from the text. Our model outperformed the state-of-the-art methods by approximately 3.97% for English to English, 1.41% for English to Hindi, 5.47% for English to Indonesian, 2.18% for English to Swahili, and 2.88% for English to Vietnamese language reviews on TALLIP fake news dataset. To the best of our knowledge, our paper is the first study that uses a capsule neural network for multilingual fake news detection.

假新闻检测是一项重要任务；然而，多种语言的复杂性使得假新闻检测具有挑战性。要理解一些虚假故事背后的逻辑，需要对众多参与者得出许多结论。现有的作品无法从特定的多语言文本语料库中的文档中收集更多的语义和上下文特征。为了克服这些挑战并处理多语言假新闻检测，我们提出了一种基于关系变量（如情绪、实体或可能直接从文本中得出的事实）识别假新闻的语义方法。在TALLIP假新闻数据集上，我们的模型在英语到英语、英语到印地语、英语到印尼语、英语和斯瓦希里语的评论中分别比最先进的方法高出约3.97%、1.41%、5.47%、2.18%和2.88%。据我们所知，我们的论文是第一个使用胶囊神经网络进行多语言假新闻检测的研究。
{"title":"Multilingual deep learning framework for fake news detection using capsule neural network.","authors":"Rami Mohawesh, Sumbal Maqsood, Qutaibah Althebyan","doi":"10.1007/s10844-023-00788-y","DOIUrl":"10.1007/s10844-023-00788-y","url":null,"abstract":"<p><p>Fake news detection is an essential task; however, the complexity of several languages makes fake news detection challenging. It requires drawing many conclusions about the numerous people involved to comprehend the logic behind some fake stories. Existing works cannot collect more semantic and contextual characteristics from documents in a particular multilingual text corpus. To bridge these challenges and deal with multilingual fake news detection, we present a semantic approach to the identification of fake news based on relational variables like sentiment, entities, or facts that may be directly derived from the text. Our model outperformed the state-of-the-art methods by approximately 3.97% for English to English, 1.41% for English to Hindi, 5.47% for English to Indonesian, 2.18% for English to Swahili, and 2.88% for English to Vietnamese language reviews on TALLIP fake news dataset. To the best of our knowledge, our paper is the first study that uses a capsule neural network for multilingual fake news detection.</p>","PeriodicalId":56119,"journal":{"name":"Journal of Intelligent Information Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10169214/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9720387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
首页 上一页
类型
全部 化学•材料 生命科学 医学 物理 工程技术 环境•农林 材料科学 地球科学 法学 管理学 化学 环境科学与生态学 计算机科学 教育学 经济学 农林科学 人文科学 生物学 数学 物理与天体物理 心理学 综合性期刊 其他 工业工程 理学 历史学 农学 文学 信息工程
数据库
全部 ACS Publications Elsevier ieeexplore Springer The Royal Society of Chemistry Wiley
期刊
Journal of Intelligent Information Systems
全部 Acc. Chem. Res. ACS Applied Bio Materials ACS Appl. Electron. Mater. ACS Appl. Energy Mater. ACS Appl. Mater. Interfaces ACS Appl. Nano Mater. ACS Appl. Polym. Mater. ACS BIOMATER-SCI ENG ACS Catal. ACS Cent. Sci. ACS Chem. Biol. ACS Chemical Health & Safety ACS Chem. Neurosci. ACS Comb. Sci. ACS Earth Space Chem. ACS Energy Lett. ACS Infect. Dis. ACS Macro Lett. ACS Mater. Lett. ACS Med. Chem. Lett. ACS Nano ACS Omega ACS Photonics ACS Sens. ACS Sustainable Chem. Eng. ACS Synth. Biol. Anal. Chem. BIOCHEMISTRY-US Bioconjugate Chem. BIOMACROMOLECULES Chem. Res. Toxicol. Chem. Rev. Chem. Mater. CRYST GROWTH DES ENERG FUEL Environ. Sci. Technol. Environ. Sci. Technol. Lett. Eur. J. Inorg. Chem. IND ENG CHEM RES Inorg. Chem. J. Agric. Food. Chem. J. Chem. Eng. Data J. Chem. Educ. J. Chem. Inf. Model. J. Chem. Theory Comput. J. Med. Chem. J. Nat. Prod. J PROTEOME RES J. Am. Chem. Soc. LANGMUIR MACROMOLECULES Mol. Pharmaceutics Nano Lett. Org. Lett. ORG PROCESS RES DEV ORGANOMETALLICS J. Org. Chem. J. Phys. Chem. J. Phys. Chem. A J. Phys. Chem. B J. Phys. Chem. C J. Phys. Chem. Lett. Analyst Anal. Methods Biomater. Sci. Catal. Sci. Technol. Chem. Commun. Chem. Soc. Rev. CHEM EDUC RES PRACT CRYSTENGCOMM Dalton Trans. Energy Environ. Sci. ENVIRON SCI-NANO ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Faraday Discuss. Food Funct. Green Chem. Inorg. Chem. Front. Integr. Biol. J. Anal. At. Spectrom. J. Mater. Chem. A J. Mater. Chem. B J. Mater. Chem. C Lab Chip Mater. Chem. Front. Mater. Horiz. MEDCHEMCOMM Metallomics Mol. Biosyst. Mol. Syst. Des. Eng. Nanoscale Nanoscale Horiz. Nat. Prod. Rep. New J. Chem. Org. Biomol. Chem. Org. Chem. Front. PHOTOCH PHOTOBIO SCI PCCP Polym. Chem.
﹀
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们：info@booksci.cn
Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1