Web Intelligence最新文献

Event type induction using latent variables with hierarchical relationship analysis 利用潜在变量和层次关系分析进行事件类型归纳

Web Intelligence Pub Date : 2024-03-20 DOI: 10.3233/web-230394

Xin Yan, Fangchang Liu, Lincheng Jiang, Youlong Long

{"title":"Event type induction using latent variables with hierarchical relationship analysis","authors":"Xin Yan, Fangchang Liu, Lincheng Jiang, Youlong Long","doi":"10.3233/web-230394","DOIUrl":"https://doi.org/10.3233/web-230394","url":null,"abstract":"The conventional approach to event extraction requires predefined event types and their corresponding annotations to train event extractors. However, these prerequisites are often difficult to satisfy in real-world applications. To automatically induct event types, most work has been devoted to clustering event triggers, where a cluster of event triggers is represented as an event type. Some works use trigger semantics, while others use co-occurrence relationships to cluster triggers. However, the clustering results of event triggers obtained by the above work are not sufficiently detailed in describing event types, making it difficult to accurately determine the corresponding event types manually. This paper proposes an open-domain event type induction framework that automatically discovers a set of event types from a given corpus. Unlike previous work on event trigger clustering, this paper takes into consideration the hierarchical relationship of event types to partition the event trigger clusters into event mains and subtypes. The framework employs a latent variable-based neural generation module and a semantic-based clustering module, the former of which obtains event trigger clusters representing the main types of events by jointly projecting the co-occurrence and semantic information of event triggers into a latent space for event type latent variable mining, and the latter of which further divides these event trigger clusters into event subtypes based on semantic information. Finally, experiment results show that, compared with the benchmark model, the ETGen-Clus can improve event type quality scores of 6.23% and 3.11% on the two datasets, respectively.","PeriodicalId":506532,"journal":{"name":"Web Intelligence","volume":"35 s143","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140224729","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

20 years of Web Intelligence: Call for a new era of AI in the Connected World 网络智能 20 年：呼唤互联世界中的人工智能新时代

Web Intelligence Pub Date : 2024-03-19 DOI: 10.3233/web-230451

Hongzhi Kuai, Xiao‐Rong Tao

引用次数: 0

Preventing malware propagation in wireless sensor networks: Hybrid optimization algorithm for controlling 防止恶意软件在无线传感器网络中传播：用于控制的混合优化算法

Web Intelligence Pub Date : 2024-02-23 DOI: 10.3233/web-230058

Madhavarapu Chandan, S. G. Santhi, T. Srinivasa Rao

{"title":"Preventing malware propagation in wireless sensor networks: Hybrid optimization algorithm for controlling","authors":"Madhavarapu Chandan, S. G. Santhi, T. Srinivasa Rao","doi":"10.3233/web-230058","DOIUrl":"https://doi.org/10.3233/web-230058","url":null,"abstract":"Malware transmission is a significant security issue in WSN, however, the influence of the attack and defensive processes on malware propagation is rarely taken into account in traditional malware propagation prevention methods. Advanced methods are in need to stop the propagation of malware of sensor nodes. With the formulation of representing dynamics among states, a new decision-making problem as the optimal control problem via hybrid optimization algorithm. The proposing model is termed as Butterfly Updated Bald Eagle Optimization based Prevention of Malware Propagation in Wireless Sensor Network (BUBEO-PMPWSN). In the proposed controlling system, optimal system parameters are analyzed via the BUBEO for preventing malware propagation in WSN. Particularly, the sensor node states considered are Susceptible, Infectious, Infectious and sleeping, recovered, Recovered and sleeping, and finally Dead. The system parameter tuning will be under the evaluation of fitness calculation under probability of infectious sensor node becoming recovered and the probability of infectious sensor node entering sleeping state. This optimal tuning strategy ensures the preventing of malware propagation. Finally, the performance of proposed BUBEO-PMPWSN model is evaluated and validated successfully by comparing other state-of-the-art models. The BUBEO-PMPWSN achieved 250 recovered nodes for time 500, while the HGS, BOA, HBA, COOT, and HHO scored 123, 115, 236, 172, and 180, respectively, for recovered nodes.","PeriodicalId":506532,"journal":{"name":"Web Intelligence","volume":"21 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140436066","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

Analysis of the effectiveness of the augmented reality technique as an influence on the digital marketing 增强现实技术对数字营销的影响效果分析

Web Intelligence Pub Date : 2024-02-22 DOI: 10.3233/web-230262

G. Gokulkumari, Ibrahim Alhassan, S. Basahel

{"title":"Analysis of the effectiveness of the augmented reality technique as an influence on the digital marketing","authors":"G. Gokulkumari, Ibrahim Alhassan, S. Basahel","doi":"10.3233/web-230262","DOIUrl":"https://doi.org/10.3233/web-230262","url":null,"abstract":"Augmented Reality is recognized as the newest clever breakthrough in marketing and is used to promote a variety of goods and services. Through the use of this technology, businesses and brands interact with their target market to learn everything about their current and potential customers’ expectations. However, important elements are associated with the development of augmented reality technology. The objective of this article is to scientifically evaluate the usefulness of virtual reality techniques in digital marketing. The study concentrated on a variety of variables, including those that influence consumers’ desire to make a purchase, such as the degree to which a system is interactive, instructive, and congruent with reality. The quantitative methodology used in this study. Random sampling methodology is used in a survey method to gather data. The partially least-squares Structured Equation Modeling (PLS-SEM) method will also be used to evaluate and confirm any proposed causal links between the latent variables. Direct marketing and system quality were shown to be correlated, and the significance value ( sig) was found to be less than 0.05. The conclusion confirms the assumption that interactivity has no significant and positive impact on digital marketing but, system quality, product informativeness, and reality congruence have a large and advantageous effect on digital marketing. Empirical findings suggest that using augmented reality technologies is one of the greatest digital marketing ways to engage customers in interactive experiences and provide them with quality goods and services.","PeriodicalId":506532,"journal":{"name":"Web Intelligence","volume":"11 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140441046","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

Deep hybrid classification model for leaf disease classification of underground crops 用于地下作物叶病分类的深度混合分类模型

Web Intelligence Pub Date : 2024-01-31 DOI: 10.3233/web-230180

R. Salini, G. Charlyn Pushpa Latha, Rashmita Khilar

{"title":"Deep hybrid classification model for leaf disease classification of underground crops","authors":"R. Salini, G. Charlyn Pushpa Latha, Rashmita Khilar","doi":"10.3233/web-230180","DOIUrl":"https://doi.org/10.3233/web-230180","url":null,"abstract":"Underground crop leave disease classification is the most significant area in the agriculture sector as they are the significant source of carbohydrates for human food. However, a disease-ridden plant could threaten the availability of food for millions of people. Researchers tried to use computer vision (CV) to develop an image classification algorithm that might warn farmers by clicking the images of plant’s leaves to find if the crop is diseased or not. This work develops anew DHCLDC model for underground crop leave disease classification that considers the plants like cassava, potato and groundnut. Here, preprocessing is done by employing median filter, followed by segmentation using Improved U-net (U-Net with nested convolutional block). Further, the features extracted comprise of color features, shape features and improved multi text on (MT) features. Finally, Hybrid classifier (HC) model is developed for DHCLDC, which comprised CNN and LSTM models. The outputs from HC(CNN + LSTM) are then given for improved score level fusion (SLF) from which final detected e are attained. Finally, simulations are done with 3 datasets to show the betterment of HC (CNN + LSTM) based DHCLDC model. The specificity of HC (CNN + LSTM) is high, at 95.41, compared to DBN, NN, RF, KNN, CNN, LSTM, DCNN, and SVM.","PeriodicalId":506532,"journal":{"name":"Web Intelligence","volume":"113 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140475402","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

A review of digital watermarking techniques: Current trends, challenges and opportunities 数字水印技术综述：当前趋势、挑战和机遇

Web Intelligence Pub Date : 2024-01-18 DOI: 10.3233/web-230280

Balkar Singh, Geeta Kasana

引用次数: 0

Analyzing the role of big data and its effects on the retail industry 分析大数据的作用及其对零售业的影响

Web Intelligence Pub Date : 2024-01-17 DOI: 10.3233/web-230027

Kameswari, P. Ramesh, Veena Bhavikatti, B. Omnamasivaya, Gorli Chaitanya, Tejeswani Bastray, Sony Hiremath, G. S. gondesi

{"title":"Analyzing the role of big data and its effects on the retail industry","authors":"Kameswari, P. Ramesh, Veena Bhavikatti, B. Omnamasivaya, Gorli Chaitanya, Tejeswani Bastray, Sony Hiremath, G. S. gondesi","doi":"10.3233/web-230027","DOIUrl":"https://doi.org/10.3233/web-230027","url":null,"abstract":"The expansion of social media, technology, and online shopping will eventually speed up massive development of retail industry. Retailing organizations are trying to figure out how the usage of big data analysis may enable them to make the correct decisions as we see Big Data as one of the buzzwords sweeping the IT world by force. Therefore, the current study’s objective is to investigate and assess the function of big data and its consequences on the retail business with the support of employees and managers from the Indian retail sector. The main factors covered in the study include big data technologies like data sources, data analysis, data storage, data security and privacy, real-time processing, and messaging system. This study employs a quantitative technique and performs Partial Least Square Structural Equation Modeling (PLS-SEM) to analyze the effects of big data in the retail sector The study findings revealed that data analysis, real-time processing, and messaging system significantly impact the performance of the retail industry whereas, data source, data storage, and data security and privacy do not significantly impact the performance of the retail industry. Various aspects discussed in the study revolving around big data technology are important factor and demands the maximum attention of the organization such as inventory utilization, customer involvement, and current value in the retail sector. The study recommends that in order to succeed, businesses of all sizes must make sure they are competitive. As internet businesses engage with their customers in real time, the rivalry heats up. Big Data analysis may benefit merchants in the following ways.","PeriodicalId":506532,"journal":{"name":"Web Intelligence","volume":" 1279","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139617011","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

Web Intelligence: In search of a better connected world 网络智能：追求更美好的互联世界

Web Intelligence Pub Date : 2024-01-15 DOI: 10.3233/web-230413

Ning Zhong, Jiming Liu, Yiyu Yao

引用次数: 0

Exploring ChatGPT for next-generation information retrieval: Opportunities and challenges 探索用于下一代信息检索的 ChatGPT：机遇与挑战

Web Intelligence Pub Date : 2024-01-12 DOI: 10.3233/web-230363

Yizheng Huang, Jimmy X. Huang

引用次数: 0

Truthful mechanisms to maximize the social welfare in real-time ride-sharing 在实时共享乘车中实现社会福利最大化的真实机制

Web Intelligence Pub Date : 2024-01-11 DOI: 10.3233/web-230401

Bing Shi, Shun Li, Yikai Luo, Liquan Zhu

{"title":"Truthful mechanisms to maximize the social welfare in real-time ride-sharing","authors":"Bing Shi, Shun Li, Yikai Luo, Liquan Zhu","doi":"10.3233/web-230401","DOIUrl":"https://doi.org/10.3233/web-230401","url":null,"abstract":"Ride-sharing contributes significantly to lowering trip expenses, easing traffic congestion and decreasing air pollution. However, current order pairing approaches in ride-sharing usually focus on minimizing total trip distances or maximizing platform profits, overlooking the drivers’ desire for increased earnings. As a result, drivers might provide dishonest information to gain higher profits, leading to inefficient order pairing for the ride-sharing platform and potential losses for both the platform and drivers. In this paper, we address this challenging issue by developing efficient order pairing mechanisms that maximize the social welfare of the platform and drivers. Specifically, we introduce two truthful auction-based order pairing mechanisms, SWMOM-VCG and SWMOM-GM, where drivers bid on platform-published orders to complete them and earn profits. We provide theoretical proof that both mechanisms fulfill the criteria of individual rationality, profitability, truthfulness and so on. Using real taxi order data from New York City, we assess the performance of both mechanisms and show that they achieve greater social welfare compared to existing methods. Additionally, we find that SWMOM-GM requires less computation time than SWMOM-VCG for order pairing, with only a minor reduction in social welfare.","PeriodicalId":506532,"journal":{"name":"Web Intelligence","volume":" 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139625958","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