图书简介
This book constitutes the proceedings of the 24th International Conference on Web Information Systems Engineering, WISE 2023, held in Melbourne, Victoria, Australia, in October 2023.The 33 full and 40 short papers were carefully reviewed and selected from 137 submissions. They were organized in topical sections as follows: text and sentiment analysis; question answering and information retrieval; social media and news analysis; security and privacy; web technologies; graph embeddings and link predictions; predictive analysis and machine learning; recommendation systems; natural language processing (NLP) and databases; data analysis and optimization; anomaly and threat detection; streaming data; miscellaneous; explainability and scalability in AI.
Text and Sentiment Analysis.- Ensemble Learning Model for Medical Text Classification.- Fuzzy Based Text Quality Assessment for Sentiment Analysis.- Prompt-Learning for Semi-Supervised Text Classification.- Label-Dependent Hypergraph Neural Network for Enhanced Multi-label Text Classification.- Fast Text Comparison Based on ElasticSearch and Dynamic Programming.- Question Answering and Information Retrieval.- User Context-aware Attention Networks for Answer Selection.- Towards Robust Token Embeddings for Extractive Question Answering.- Math Information Retrieval with Contrastive Learning of Formula Embeddings.- Social Media and News Analysis.- Influence Embedding from Incomplete Observations in Sina Weibo.- Dissemination of Fact-checked News does not Combat False News: Empirical Analysis.- Highly Applicable Linear Event Detection Algorithm on Social Media with Graph Stream.- Leveraging Social Networks for Mergers and Acquisitions Forecasting.- Enhancing Trust Prediction in Attributed Social Networks with Self-Supervised Learning.- Security and Privacy.- Bilateral Insider Threat Detection: Harnessing Standalone and Sequential Activities with Recurrent Neural Networks.- ATDG: An Automatic Cyber Threat Intelligence Extraction Model of DPCNN and BIGRU Combined with Attention Mechanism.- Blockchain-Empowered Resource Allocation and Data Security for Efficient Vehicle Edge Computing.- Priv-S: Privacy-Sensitive Data Identification in Online Social Networks.- TLEF: Two-Layer Evolutionary Framework for t-closeness Anonymization.- A Dual-Layer Privacy-Preserving Federated Learning Framework.- A Privacy-Preserving Evolutionary Computation Framework for Feature Selection.- Local Difference-based Federated Learning Against Preference Profiling Attacks.- Proximity-based MAENS: A Computational Intelligence Method for Privacy-Preserving Multiple Traveling Salesmen Problem.- Empowering Vulnerability Prioritization: A Heterogeneous Graph-Driven Framework for Exploitability Prediction.- ICAD: An Intelligent Framework for Real-Time Criminal Analytics and Detection.- Web Technologies.- Web Page Segmentation: A DOM-structural Cohesion Analysis Approach.- Learning to Select the Relevant History Turns in Conversational Question Answering.- A Methodological Approach for Data-intensive Web Application Design on top of Data Lakes.- ESPRESSO: A Framework for Empowering Search on Decentralized Web.- Primary Building Blocks for Web Automation.- A Web Service Oriented Integration Solution for Capital Facilities Information Handover.- Deep Neural Network based approach for IoT service QoS prediction.- Graph Embeddings and Link Predictions.- Path-KGE: Preference-aware Knowledge Graph Embedding with Path Semantics for Link Prediction.- Efficient Graph Embedding Method for Link Prediction via Incorporating Graph Structure and Node Attributes.- Link Prediction for Opportunistic Networks Based on Hybrid Similarity Metrics and E-LSTM-D Models.- FastAGEDs: Fast Approximate Graph Entity Dependency Discovery.- Topological Network Field Preservation For Heterogeneous Graph Embedding.- Predictive Analysis and Machine Learning.- Federated Learning Performance on Early ICU Mortality Prediction with Extreme Data Distributions.- TSEGformer:Time-Space dimension dependency transformer for use in multivariate time series prediction.- Fraudulent Jobs Prediction Using Natural Language Processing and Deep Learning Sequential Models.- Prediction of Student Performance with Machine Learning Algorithms
Trade Policy 买家须知
- 关于产品:
- ● 正版保障:本网站隶属于中国国际图书贸易集团公司,确保所有图书都是100%正版。
- ● 环保纸张:进口图书大多使用的都是环保轻型张,颜色偏黄,重量比较轻。
- ● 毛边版:即书翻页的地方,故意做成了参差不齐的样子,一般为精装版,更具收藏价值。
关于退换货:
- 由于预订产品的特殊性,采购订单正式发订后,买方不得无故取消全部或部分产品的订购。
- 由于进口图书的特殊性,发生以下情况的,请直接拒收货物,由快递返回:
- ● 外包装破损/发错货/少发货/图书外观破损/图书配件不全(例如:光盘等)
并请在工作日通过电话400-008-1110联系我们。
- 签收后,如发生以下情况,请在签收后的5个工作日内联系客服办理退换货:
- ● 缺页/错页/错印/脱线
关于发货时间:
- 一般情况下:
- ●【现货】 下单后48小时内由北京(库房)发出快递。
- ●【预订】【预售】下单后国外发货,到货时间预计5-8周左右,店铺默认中通快递,如需顺丰快递邮费到付。
- ● 需要开具发票的客户,发货时间可能在上述基础上再延后1-2个工作日(紧急发票需求,请联系010-68433105/3213);
- ● 如遇其他特殊原因,对发货时间有影响的,我们会第一时间在网站公告,敬请留意。
关于到货时间:
- 由于进口图书入境入库后,都是委托第三方快递发货,所以我们只能保证在规定时间内发出,但无法为您保证确切的到货时间。
- ● 主要城市一般2-4天
- ● 偏远地区一般4-7天
关于接听咨询电话的时间:
- 010-68433105/3213正常接听咨询电话的时间为:周一至周五上午8:30~下午5:00,周六、日及法定节假日休息,将无法接听来电,敬请谅解。
- 其它时间您也可以通过邮件联系我们:customer@readgo.cn,工作日会优先处理。
关于快递:
- ● 已付款订单:主要由中通、宅急送负责派送,订单进度查询请拨打010-68433105/3213。
本书暂无推荐
本书暂无推荐