International Journal of Web Information Systems最新文献_第2页

Graph-based multi-information integration network with external news environment perception for Propaganda detection 基于外部新闻环境感知的图式多信息集成网络用于宣传检测

IF 1.6

International Journal of Web Information Systems Pub Date : 2024-02-15 DOI: 10.1108/ijwis-12-2023-0242

Xinyu Liu, Kun Ma, Ke Ji, Zhenxiang Chen, Bo Yang

{"title":"Graph-based multi-information integration network with external news environment perception for Propaganda detection","authors":"Xinyu Liu, Kun Ma, Ke Ji, Zhenxiang Chen, Bo Yang","doi":"10.1108/ijwis-12-2023-0242","DOIUrl":"https://doi.org/10.1108/ijwis-12-2023-0242","url":null,"abstract":"\u0000Purpose\u0000Propaganda is a prevalent technique used in social media to intentionally express opinions or actions with the aim of manipulating or deceiving users. Existing methods for propaganda detection primarily focus on capturing language features within its content. However, these methods tend to overlook the information presented within the external news environment from which propaganda news originated and spread. This news environment reflects recent mainstream media opinions and public attention and contains language characteristics of non-propaganda news. Therefore, the authors have proposed a graph-based multi-information integration network with an external news environment (abbreviated as G-MINE) for propaganda detection.\u0000\u0000\u0000Design/methodology/approach\u0000G-MINE is proposed to comprise four parts: textual information extraction module, external news environment perception module, multi-information integration module and classifier. Specifically, the external news environment perception module and multi-information integration module extract and integrate the popularity and novelty into the textual information and capture the high-order complementary information between them.\u0000\u0000\u0000Findings\u0000G-MINE achieves state-of-the-art performance on both the TSHP-17, Qprop and the PTC data sets, with an accuracy of 98.24%, 90.59% and 97.44%, respectively.\u0000\u0000\u0000Originality/value\u0000An external news environment perception module is proposed to capture the popularity and novelty information, and a multi-information integration module is proposed to effectively fuse them with the textual information.\u0000","PeriodicalId":44153,"journal":{"name":"International Journal of Web Information Systems","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139775683","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

Chain-of-event prompting for multi-document summarization by large language models 通过大型语言模型进行多文档摘要的事件链提示

IF 1.6

International Journal of Web Information Systems Pub Date : 2024-02-15 DOI: 10.1108/ijwis-12-2023-0249

Songlin Bao, Tiantian Li, Bin Cao

{"title":"Chain-of-event prompting for multi-document summarization by large language models","authors":"Songlin Bao, Tiantian Li, Bin Cao","doi":"10.1108/ijwis-12-2023-0249","DOIUrl":"https://doi.org/10.1108/ijwis-12-2023-0249","url":null,"abstract":"\u0000Purpose\u0000In the era of big data, various industries are generating large amounts of text data every day. Simplifying and summarizing these data can effectively serve users and improve efficiency. Recently, zero-shot prompting in large language models (LLMs) has demonstrated remarkable performance on various language tasks. However, generating a very “concise” multi-document summary is a difficult task for it. When conciseness is specified in the zero-shot prompting, the generated multi-document summary still contains some unimportant information, even with the few-shot prompting. This paper aims to propose a LLMs prompting for multi-document summarization task.\u0000\u0000\u0000Design/methodology/approach\u0000To overcome this challenge, the authors propose chain-of-event (CoE) prompting for multi-document summarization (MDS) task. In this prompting, the authors take events as the center and propose a four-step summary reasoning process: specific event extraction; event abstraction and generalization; common event statistics; and summary generation. To further improve the performance of LLMs, the authors extend CoE prompting with the example of summary reasoning.\u0000\u0000\u0000Findings\u0000Summaries generated by CoE prompting are more abstractive, concise and accurate. The authors evaluate the authors’ proposed prompting on two data sets. The experimental results over ChatGLM2-6b show that the authors’ proposed CoE prompting consistently outperforms other typical promptings across all data sets.\u0000\u0000\u0000Originality/value\u0000This paper proposes CoE prompting to solve MDS tasks by the LLMs. CoE prompting can not only identify the key events but also ensure the conciseness of the summary. By this method, users can access the most relevant and important information quickly, improving their decision-making processes.\u0000","PeriodicalId":44153,"journal":{"name":"International Journal of Web Information Systems","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139835058","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

Chain-of-event prompting for multi-document summarization by large language models 通过大型语言模型进行多文档摘要的事件链提示

IF 1.6

International Journal of Web Information Systems Pub Date : 2024-02-15 DOI: 10.1108/ijwis-12-2023-0249

Songlin Bao, Tiantian Li, Bin Cao

{"title":"Chain-of-event prompting for multi-document summarization by large language models","authors":"Songlin Bao, Tiantian Li, Bin Cao","doi":"10.1108/ijwis-12-2023-0249","DOIUrl":"https://doi.org/10.1108/ijwis-12-2023-0249","url":null,"abstract":"\u0000Purpose\u0000In the era of big data, various industries are generating large amounts of text data every day. Simplifying and summarizing these data can effectively serve users and improve efficiency. Recently, zero-shot prompting in large language models (LLMs) has demonstrated remarkable performance on various language tasks. However, generating a very “concise” multi-document summary is a difficult task for it. When conciseness is specified in the zero-shot prompting, the generated multi-document summary still contains some unimportant information, even with the few-shot prompting. This paper aims to propose a LLMs prompting for multi-document summarization task.\u0000\u0000\u0000Design/methodology/approach\u0000To overcome this challenge, the authors propose chain-of-event (CoE) prompting for multi-document summarization (MDS) task. In this prompting, the authors take events as the center and propose a four-step summary reasoning process: specific event extraction; event abstraction and generalization; common event statistics; and summary generation. To further improve the performance of LLMs, the authors extend CoE prompting with the example of summary reasoning.\u0000\u0000\u0000Findings\u0000Summaries generated by CoE prompting are more abstractive, concise and accurate. The authors evaluate the authors’ proposed prompting on two data sets. The experimental results over ChatGLM2-6b show that the authors’ proposed CoE prompting consistently outperforms other typical promptings across all data sets.\u0000\u0000\u0000Originality/value\u0000This paper proposes CoE prompting to solve MDS tasks by the LLMs. CoE prompting can not only identify the key events but also ensure the conciseness of the summary. By this method, users can access the most relevant and important information quickly, improving their decision-making processes.\u0000","PeriodicalId":44153,"journal":{"name":"International Journal of Web Information Systems","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139775617","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

Graph-based multi-information integration network with external news environment perception for Propaganda detection 基于外部新闻环境感知的图式多信息集成网络用于宣传检测

IF 1.6

International Journal of Web Information Systems Pub Date : 2024-02-15 DOI: 10.1108/ijwis-12-2023-0242

Xinyu Liu, Kun Ma, Ke Ji, Zhenxiang Chen, Bo Yang

{"title":"Graph-based multi-information integration network with external news environment perception for Propaganda detection","authors":"Xinyu Liu, Kun Ma, Ke Ji, Zhenxiang Chen, Bo Yang","doi":"10.1108/ijwis-12-2023-0242","DOIUrl":"https://doi.org/10.1108/ijwis-12-2023-0242","url":null,"abstract":"\u0000Purpose\u0000Propaganda is a prevalent technique used in social media to intentionally express opinions or actions with the aim of manipulating or deceiving users. Existing methods for propaganda detection primarily focus on capturing language features within its content. However, these methods tend to overlook the information presented within the external news environment from which propaganda news originated and spread. This news environment reflects recent mainstream media opinions and public attention and contains language characteristics of non-propaganda news. Therefore, the authors have proposed a graph-based multi-information integration network with an external news environment (abbreviated as G-MINE) for propaganda detection.\u0000\u0000\u0000Design/methodology/approach\u0000G-MINE is proposed to comprise four parts: textual information extraction module, external news environment perception module, multi-information integration module and classifier. Specifically, the external news environment perception module and multi-information integration module extract and integrate the popularity and novelty into the textual information and capture the high-order complementary information between them.\u0000\u0000\u0000Findings\u0000G-MINE achieves state-of-the-art performance on both the TSHP-17, Qprop and the PTC data sets, with an accuracy of 98.24%, 90.59% and 97.44%, respectively.\u0000\u0000\u0000Originality/value\u0000An external news environment perception module is proposed to capture the popularity and novelty information, and a multi-information integration module is proposed to effectively fuse them with the textual information.\u0000","PeriodicalId":44153,"journal":{"name":"International Journal of Web Information Systems","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139835359","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

LCPCWSC: a Web service classification approach based on label confusion and priori correction LCPCWSC：基于标签混淆和先验校正的网络服务分类方法

IF 1.6

International Journal of Web Information Systems Pub Date : 2024-02-06 DOI: 10.1108/ijwis-12-2023-0243

Lin Xue, Feng Zhang

{"title":"LCPCWSC: a Web service classification approach based on label confusion and priori correction","authors":"Lin Xue, Feng Zhang","doi":"10.1108/ijwis-12-2023-0243","DOIUrl":"https://doi.org/10.1108/ijwis-12-2023-0243","url":null,"abstract":"\u0000Purpose\u0000With the increasing number of Web services, correct and efficient classification of Web services is crucial to improve the efficiency of service discovery. However, existing Web service classification approaches ignore the class overlap in Web services, resulting in poor accuracy of classification in practice. This paper aims to provide an approach to address this issue.\u0000\u0000\u0000Design/methodology/approach\u0000This paper proposes a label confusion and priori correction-based Web service classification approach. First, functional semantic representations of Web services descriptions are obtained based on BERT. Then, the ability of the model is enhanced to recognize and classify overlapping instances by using label confusion learning techniques; Finally, the predictive results are corrected based on the label prior distribution to further improve service classification effectiveness.\u0000\u0000\u0000Findings\u0000Experiments based on the ProgrammableWeb data set show that the proposed model demonstrates 4.3%, 3.2% and 1% improvement in Macro-F1 value compared to the ServeNet-BERT, BERT-DPCNN and CARL-NET, respectively.\u0000\u0000\u0000Originality/value\u0000This paper proposes a Web service classification approach for the overlapping categories of Web services and improve the accuracy of Web services classification.\u0000","PeriodicalId":44153,"journal":{"name":"International Journal of Web Information Systems","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139800730","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

LCPCWSC: a Web service classification approach based on label confusion and priori correction LCPCWSC：基于标签混淆和先验校正的网络服务分类方法

IF 1.6

International Journal of Web Information Systems Pub Date : 2024-02-06 DOI: 10.1108/ijwis-12-2023-0243

Lin Xue, Feng Zhang

{"title":"LCPCWSC: a Web service classification approach based on label confusion and priori correction","authors":"Lin Xue, Feng Zhang","doi":"10.1108/ijwis-12-2023-0243","DOIUrl":"https://doi.org/10.1108/ijwis-12-2023-0243","url":null,"abstract":"\u0000Purpose\u0000With the increasing number of Web services, correct and efficient classification of Web services is crucial to improve the efficiency of service discovery. However, existing Web service classification approaches ignore the class overlap in Web services, resulting in poor accuracy of classification in practice. This paper aims to provide an approach to address this issue.\u0000\u0000\u0000Design/methodology/approach\u0000This paper proposes a label confusion and priori correction-based Web service classification approach. First, functional semantic representations of Web services descriptions are obtained based on BERT. Then, the ability of the model is enhanced to recognize and classify overlapping instances by using label confusion learning techniques; Finally, the predictive results are corrected based on the label prior distribution to further improve service classification effectiveness.\u0000\u0000\u0000Findings\u0000Experiments based on the ProgrammableWeb data set show that the proposed model demonstrates 4.3%, 3.2% and 1% improvement in Macro-F1 value compared to the ServeNet-BERT, BERT-DPCNN and CARL-NET, respectively.\u0000\u0000\u0000Originality/value\u0000This paper proposes a Web service classification approach for the overlapping categories of Web services and improve the accuracy of Web services classification.\u0000","PeriodicalId":44153,"journal":{"name":"International Journal of Web Information Systems","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139860488","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

TN-MR: topic-aware neural network-based mobile application recommendation TN-MR：基于主题感知神经网络的移动应用推荐

IF 1.6

International Journal of Web Information Systems Pub Date : 2024-02-06 DOI: 10.1108/ijwis-10-2023-0205

Junyi Chen, Buqing Cao, Zhenlian Peng, Ziming Xie, Shanpeng Liu, Qian Peng

{"title":"TN-MR: topic-aware neural network-based mobile application recommendation","authors":"Junyi Chen, Buqing Cao, Zhenlian Peng, Ziming Xie, Shanpeng Liu, Qian Peng","doi":"10.1108/ijwis-10-2023-0205","DOIUrl":"https://doi.org/10.1108/ijwis-10-2023-0205","url":null,"abstract":"\u0000Purpose\u0000With the increasing number of mobile applications, efficiently recommending mobile applications to users has become a challenging problem. Although existing mobile application recommendation approaches based on user attributes and behaviors have achieved notable effectiveness, they overlook the diffusion patterns and interdependencies of topic-specific mobile applications among user groups. mobile applications among user groups. This paper aims to capture the diffusion patterns and interdependencies of mobile applications among user groups. To achieve this, a topic-aware neural network-based mobile application recommendation method, referred to as TN-MR, is proposed.\u0000\u0000\u0000Design/methodology/approach\u0000In this method, first, the user representations are enhanced by introducing a topic-aware attention layer, which captures both the topic context and the diffusion history context. Second, it exploits a time-decay mechanism to simulate changes in user interest. Multitopic user representations are aggregated by the time decay module to output the user representations of cascading representations under multiple topics. Finally, user scores that are likely to download the mobile application are predicted and ranked.\u0000\u0000\u0000Findings\u0000Experimental comparisons and analyses were conducted on the actual 360App data set, and the results demonstrate that the effectiveness of mobile application recommendations can be significantly improved by using TN-MR.\u0000\u0000\u0000Originality/value\u0000In this paper, the authors propose a mobile application recommendation method based on topic-aware attention networks. By capturing the diffusion patterns and dependencies of mobile applications, it effectively assists users in selecting their applications of interest from thousands of options, significantly improving the accuracy of mobile application recommendations.\u0000","PeriodicalId":44153,"journal":{"name":"International Journal of Web Information Systems","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139683038","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

Cross-lingual speaker transfer for Cambodian based on feature disentangler and time-frequency attention adaptive normalization 基于特征分离器和时频注意自适应归一化的柬埔寨语跨语言演讲者转移

IF 1.6

International Journal of Web Information Systems Pub Date : 2024-01-26 DOI: 10.1108/ijwis-09-2023-0162

Yuanzhang Yang, Linqin Wang, Shengxiang Gao, Zhengtao Yu, Ling Dong

引用次数: 0

DoS attack detection using Aquila deer hunting optimization enabled deep belief network 利用 Aquila 猎鹿优化深度信念网络检测 DoS 攻击

IF 1.6

International Journal of Web Information Systems Pub Date : 2024-01-26 DOI: 10.1108/ijwis-06-2023-0089

Merly Thomas, Meshram B.B.

引用次数: 0

User credibility evaluation for reputation measurement of online service 用于衡量在线服务声誉的用户可信度评价

IF 1.6

International Journal of Web Information Systems Pub Date : 2024-01-18 DOI: 10.1108/ijwis-12-2023-0247

Yahan Xiong, Xiaodong Fu

{"title":"User credibility evaluation for reputation measurement of online service","authors":"Yahan Xiong, Xiaodong Fu","doi":"10.1108/ijwis-12-2023-0247","DOIUrl":"https://doi.org/10.1108/ijwis-12-2023-0247","url":null,"abstract":"\u0000Purpose\u0000Users often struggle to select choosing among similar online services. To help them make informed decisions, it is important to establish a service reputation measurement mechanism. User-provided feedback ratings serve as a primary source of information for this mechanism, and ensuring the credibility of user feedback is crucial for a reliable reputation measurement. Most of the previous studies use passive detection to identify false feedback without creating incentives for honest reporting. Therefore, this study aims to develop a reputation measure for online services that can provide incentives for users to report honestly.\u0000\u0000\u0000Design/methodology/approach\u0000In this paper, the authors present a method that uses a peer prediction mechanism to evaluate user credibility, which evaluates users’ credibility with their reports by applying the strictly proper scoring rule. Considering the heterogeneity among users, the authors measure user similarity, identify similar users as peers to assess credibility and calculate service reputation using an improved expectation-maximization algorithm based on user credibility.\u0000\u0000\u0000Findings\u0000Theoretical analysis and experimental results verify that the proposed method motivates truthful reporting, effectively identifies malicious users and achieves high service rating accuracy.\u0000\u0000\u0000Originality/value\u0000The proposed method has significant practical value in evaluating the authenticity of user feedback and promoting honest reporting.\u0000","PeriodicalId":44153,"journal":{"name":"International Journal of Web Information Systems","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139526226","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