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  • A Pseudo-document-based Topical N-grams model for short texts
    World Wide Web (IF 2.892) Pub Date : 2020-07-23
    Hao Lin, Yuan Zuo, Guannan Liu, Hong Li, Junjie Wu, Zhiang Wu

    In recent years, short text topic modeling has drawn considerable attentions from interdisciplinary researchers. Various customized topic models have been proposed to tackle the semantic sparseness nature of short texts. Most (if not all) of them follow the bag-of-words assumption, which, however, is not adequate since word order and phrases are often critical to capturing the meaning of texts. On

    更新日期:2020-07-23
  • Let’s CoRank: trust of users and tweets on social networks
    World Wide Web (IF 2.892) Pub Date : 2020-07-14
    Peiyao Li, Weiliang Zhao, Jian Yang, Quan Z. Sheng, Jia Wu

    Twitter, as one of the largest Online Social Network (OSN) platforms, is a popular media for online social communication and information dissemination. The trustworthy evaluation of information and people becomes crucial for maintaining an open and healthy OSN for our society. In this work, we develop a Coupled Dual Networks Trust Ranking (CoRank) method to evaluate the trustworthiness of users and

    更新日期:2020-07-14
  • Indexing and progressive top- k similarity retrieval of trajectories
    World Wide Web (IF 2.892) Pub Date : 2020-07-06
    Nikolaos Pliakis, Eleftherios Tiakas, Yannis Manolopoulos

    In this work, we study the performance of state-of-the-art access methods to efficiently store and retrieve trajectories in spatial networks. First, we study how efficiently such methods can manage trajectory data to support indexing for data demanding applications where trajectory retrieval must be fast. At the same time, trajectory insertions, deletions and modifications should also be executed efficiently

    更新日期:2020-07-06
  • Constructing dummy query sequences to protect location privacy and query privacy in location-based services
    World Wide Web (IF 2.892) Pub Date : 2020-07-06
    Zongda Wu, Guiling Li, Shigen Shen, Xinze Lian, Enhong Chen, Guandong Xu

    Location-based services (LBS) have become an important part of people’s daily life. However, while providing great convenience for mobile users, LBS result in a serious problem on personal privacy, i.e., location privacy and query privacy. However, existing privacy methods for LBS generally take into consideration only location privacy or query privacy, without considering the problem of protecting

    更新日期:2020-07-06
  • Towards distributed node similarity search on graphs
    World Wide Web (IF 2.892) Pub Date : 2020-06-18
    Tianming Zhang, Yunjun Gao, Baihua Zheng, Lu Chen, Shiting Wen, Wei Guo

    Node similarity search on graphs has wide applications in recommendation, link prediction, to name just a few. However, existing studies are insufficient due to two reasons: (i) the scale of the real-world graph is growing rapidly, and (ii) vertices are always associated with complex attributes. In this paper, we propose an efficiently distributed framework to support node similarity search on massive

    更新日期:2020-06-18
  • Fine-grained emotion classification of Chinese microblogs based on graph convolution networks
    World Wide Web (IF 2.892) Pub Date : 2020-06-17
    Yuni Lai, Linfeng Zhang, Donghong Han, Rui Zhou, Guoren Wang

    Microblogs are widely used to express people’s opinions and feelings in daily life. Sentiment analysis (SA) can timely detect personal sentiment polarities through analyzing text. Deep learning approaches have been broadly used in SA but still have not fully exploited syntax information. In this paper, we propose a syntax-based graph convolution network (GCN) model to enhance the understanding of diverse

    更新日期:2020-06-17
  • Topic representation model based on microblogging behavior analysis
    World Wide Web (IF 2.892) Pub Date : 2020-06-15
    Weihong Han, Zhihong Tian, Zizhong Huang, Shudong Li, Yan Jia

    With the development of microblogging, it has become an important way for people to obtain information, express opinions, and make suggestions. Identifying new topics quickly and accurately from the massive microblogging data plays a crucial role for recommending information and controlling public opinion. The topic representation model provides a basis for topic detection. In this paper, we propose

    更新日期:2020-06-15
  • Why current differential privacy schemes are inapplicable for correlated data publishing?
    World Wide Web (IF 2.892) Pub Date : 2020-06-08
    Hao Wang, Zhengquan Xu, Shan Jia, Ying Xia, Xu Zhang

    Although data analysis and mining technologies can efficiently provide intelligent and personalized services to us, data owners may not always be willing to share their true data because of privacy concerns. Recently, differential privacy (DP) technology has achieved a good trade-off between data utility and privacy guarantee by publishing noisy outputs. Nonetheless, DP still has a risk of privacy

    更新日期:2020-06-08
  • Generative temporal link prediction via self-tokenized sequence modeling
    World Wide Web (IF 2.892) Pub Date : 2020-05-29
    Yue Wang, Chenwei Zhang, Shen Wang, Philip S. Yu, Lu Bai, Lixin Cui, Guandong Xu

    We formalize networks with evolving structures as temporal networks and propose a generative link prediction model, Generative Link Sequence Modeling (GLSM), to predict future links for temporal networks. GLSM captures the temporal link formation patterns from the observed links with a sequence modeling framework and has the ability to generate the emerging links by inferring from the probability distribution

    更新日期:2020-05-29
  • Accurate relational reasoning in edge-labeled graphs by multi-labeled random walk with restart
    World Wide Web (IF 2.892) Pub Date : 2020-05-21
    Jinhong Jung, Woojeong Jin, Ha-myung Park, U Kang

    Given an edge-labeled graph and two nodes, how can we accurately infer the relation between the nodes? Reasoning how the nodes are related is a fundamental task in analyzing network data, and various relevance measures have been suggested to effectively identify relevance between nodes in graphs. Although many random walk based models have been extensively utilized to reveal relevance between nodes

    更新日期:2020-05-21
  • Extracting diverse-shapelets for early classification on time series
    World Wide Web (IF 2.892) Pub Date : 2020-05-21
    Wenhe Yan, Guiling Li, Zongda Wu, Senzhang Wang, Philip S. Yu

    In recent years, early classification on time series has become increasingly important in time-sensitive applications. Existing shapelet based methods still cannot work well on this problem. First, the effectiveness of traditional shapelet based methods would be influenced by the number of shapelet candidates. Second, it is difficult for previous methods to obtain diverse shapelets in shapelet selection

    更新日期:2020-05-21
  • Multi-document semantic relation extraction for news analytics
    World Wide Web (IF 2.892) Pub Date : 2020-05-18
    Yongpan Sheng, Zenglin Xu, Yafang Wang, Gerard de Melo

    Given the overwhelming amounts of information in our current 24/7 stream of new incoming articles, new techniques are needed to enable users to focus on just the key entities and concepts along with their relationships. Examples include news articles but also business reports and social media. The fact that relevant information may be distributed across diverse sources makes it particularly challenging

    更新日期:2020-05-18
  • Yet another approach to understanding news event evolution
    World Wide Web (IF 2.892) Pub Date : 2020-05-05
    Shangwen Lv, Longtao Huang, Liangjun Zang, Wei Zhou, Jizhong Han, Songlin Hu

    With information explosion on the Internet, only returning ranked documents by search engines cannot satisfy people’s requirements on news events understanding. A more intelligent news events search engine should not only retrieve all related documents about a specific event, but also provide a global view about how the event originates and evolves. In order to solve this challenge, two tasks, event

    更新日期:2020-05-05
  • DP-FL: a novel differentially private federated learning framework for the unbalanced data
    World Wide Web (IF 2.892) Pub Date : 2020-04-30
    Xixi Huang, Ye Ding, Zoe L. Jiang, Shuhan Qi, Xuan Wang, Qing Liao

    Security issues of artificial intelligence attract many attention in many research fields and industries, such as face recognition, medical care, and client services. Federated learning is proposed by Google, which can prevent the leakage of data during the AI training because each enterprise only needs to exchange training parameters without data sharing. In this paper, we present a novel differentially

    更新日期:2020-04-30
  • End-to-end relation extraction based on bootstrapped multi-level distant supervision
    World Wide Web (IF 2.892) Pub Date : 2020-04-24
    Ying He, Zhixu Li, Qiang Yang, Zhigang Chen, An Liu, Lei Zhao, Xiaofang Zhou

    Distant supervised relation extraction has been widely used to identify new relation facts from free text, since the existence of knowledge base helps these models to build a large dataset with few human intervention and low costs of manpower and time. However, the existing Distant Supervised models are all based on the single-node classifier so that they suffer from the serious false categorization

    更新日期:2020-04-24
  • Decision-based evasion attacks on tree ensemble classifiers
    World Wide Web (IF 2.892) Pub Date : 2020-04-20
    Fuyong Zhang, Yi Wang, Shigang Liu, Hua Wang

    Learning-based classifiers are found to be susceptible to adversarial examples. Recent studies suggested that ensemble classifiers tend to be more robust than single classifiers against evasion attacks. In this paper, we argue that this is not necessarily the case. In particular, we show that a discrete-valued random forest classifier can be easily evaded by adversarial inputs manipulated based only

    更新日期:2020-04-20
  • Rebalancing the car-sharing system with reinforcement learning
    World Wide Web (IF 2.892) Pub Date : 2020-04-20
    Changwei Ren, Lixingjian An, Zhanquan Gu, Yuexuan Wang, Yunjun Gao

    With the sharing economy boom, there is a notable increase in the number of car-sharing corporations, which provided a variety of travel options and improved convenience and functionality. Owing to the similarity in the travel patterns of the urban population, car-sharing system often faces the problem of imbalance in the number of shared cars within the spatial distribution, especially during the

    更新日期:2020-04-20
  • Embedding geographic information for anomalous trajectory detection
    World Wide Web (IF 2.892) Pub Date : 2020-04-17
    Ding Xiao, Li Song, Ruijia Wang, Xiaotian Han, Yanan Cai, Chuan Shi

    Anomalous trajectory detection is a crucial task in trajectory mining fields. Traditional anomalous trajectory detection methods mainly focus on the differences of a new trajectory and the historical trajectory with density and isolation techniques, which may suffer from the following two disadvantages. (1) They cannot capture the sequential information of the trajectory well. (2) They cannot make

    更新日期:2020-04-18
  • Understanding a bag of words by conceptual labeling with prior weights
    World Wide Web (IF 2.892) Pub Date : 2020-04-14
    Haiyun Jiang, Deqing Yang, Yanghua Xiao, Wei Wang

    Abstract In many natural language processing tasks, e.g., text classification or information extraction, the weighted bag-of-words model is widely used to represent the semantics of text, where the importance of each word is quantified by its weight. However, it is still difficult for machines to understand a weighted bag of words (WBoW) without explicit explanations, which seriously limits its application

    更新日期:2020-04-14
  • A detailed review of D2D cache in helper selection
    World Wide Web (IF 2.892) Pub Date : 2020-04-11
    Tong Wang, Yunfeng Wang, Xibo Wang, Yue Cao

    Abstract With the rapid development of communication networks, the information interaction between heterogeneous networks such as the Internet of Things (IoT) and vehicle ad-hoc networks (VANETs) is becoming more and more common. In cellular networks, the proximity devices may share files directly without going through the eNBs, which is named Device-to-Device (D2D) communications. It has been considered

    更新日期:2020-04-14
  • Multi-source knowledge fusion: a survey
    World Wide Web (IF 2.892) Pub Date : 2020-04-08
    Xiaojuan Zhao, Yan Jia, Aiping Li, Rong Jiang, Yichen Song

    Abstract Multi-source knowledge fusion is one of the important research topics in the fields of artificial intelligence, natural language processing, and so on. The research results of multi-source knowledge fusion can help computer to better understand human intelligence, human language and human thinking, effectively promote the Big Search in Cyberspace, effectively promote the construction of domain

    更新日期:2020-04-14
  • Flexible sensitive K -anonymization on transactions
    World Wide Web (IF 2.892) Pub Date : 2020-04-01
    Yu-Chuan Tsai, Shyue-Liang Wang, I-Hsien Ting, Tzung-Pei Hong

    Abstract In recent years, privacy breaches have been a great concern on the published data. Only removing one’s personal identification information is not sufficient to protect individual’s privacy. Privacy preservation technology for published data is devoted to preventing re-identification and retaining the useful information in published data. In this work, we propose a novel algorithm to deal with

    更新日期:2020-04-14
  • Personalized top- n influential community search over large social networks
    World Wide Web (IF 2.892) Pub Date : 2020-03-31
    Jian Xu, Xiaoyi Fu, Yiming Wu, Ming Luo, Ming Xu, Ning Zheng

    Abstract User-centered analysis is one of the aims of online community search. In this paper, we study personalized top-n influential community search that has a practical application. Given an evolving social network, where every edge has a propagation probability, we propose a maximal pk-Clique community model, that uses a new cohesive criterion. The criterion requires that the propagation probability

    更新日期:2020-04-14
  • Scene text reading based cloud compliance access
    World Wide Web (IF 2.892) Pub Date : 2020-03-31
    Hezhong Pan, Chuanyi Liu, Shaoming Duan, Peiyi Han, Binxing Fang

    Abstract Cloud Compliance Access system assure that cloud users could utilize resources of cloud platform while conforming to regulations and the specific functions of this system were User Behavior Analyze and Data Sanitization. However, the problem of information extraction from images data is still to be addressed for both of these functions. The authors, in this paper, ventures to propose a new

    更新日期:2020-04-14
  • Measurement and analysis on large-scale offline mobile app dissemination over device-to-device sharing in mobile social networks
    World Wide Web (IF 2.892) Pub Date : 2020-03-27
    Xiaofei Wang, Chenyang Wang, Xu Chen, Xiaoming Fu, Jinyoung Han, Xin Wang

    Abstract Recently, the issue of offloading cellular data while reducing the duplicated cellular transmission has gained more and more attention. Several studies have shown that sharing contents through Device-to-Device (D2D) to offload traffic to local connections nearby can offer better performance for mobile users. Nevertheless, most existing proposals are somewhat confined to small-scale data sets

    更新日期:2020-04-14
  • Topic based time-sensitive influence maximization in online social networks
    World Wide Web (IF 2.892) Pub Date : 2020-03-26
    Huiyu Min, Jiuxin Cao, Tangfei Yuan, Bo Liu

    Abstract With the exponential expansion of online social networks (OSNs), an extensive research on information diffusion in OSNs has been emerged in recent years. One of the key research is influence maximization (IM). IM is a problem to find a seed set with k nodes, so as to maximize the range of information propagation in OSNs. Most research adopts general greedy, degree discount, and centrality

    更新日期:2020-04-14
  • Mining health knowledge graph for health risk prediction
    World Wide Web (IF 2.892) Pub Date : 2020-03-20
    Xiaohui Tao, Thuan Pham, Ji Zhang, Jianming Yong, Wee Pheng Goh, Wenping Zhang, Yi Cai

    Abstract Nowadays classification models have been widely adopted in healthcare, aiming at supporting practitioners for disease diagnosis and human error reduction. The challenge is utilising effective methods to mine real-world data in the medical domain, as many different models have been proposed with varying results. A large number of researchers focus on the diversity problem of real-time data

    更新日期:2020-04-14
  • Efficient targeted influence minimization in big social networks
    World Wide Web (IF 2.892) Pub Date : 2020-03-19
    Xinjue Wang, Ke Deng, Jianxin Li, Jeffery Xu Yu, Christian S. Jensen, Xiaochun Yang

    Abstract An online social network can be used for the diffusion of malicious information like derogatory rumors, disinformation, hate speech, revenge pornography, etc. This motivates the study of influence minimization that aim to prevent the spread of malicious information. Unlike previous influence minimization work, this study considers the influence minimization in relation to a particular group

    更新日期:2020-04-14
  • Web event evolution trend prediction based on its computational social context
    World Wide Web (IF 2.892) Pub Date : 2020-03-14
    Junyu Xuan, Xiangfeng Luo, Jie Lu, Guangquan Zhang

    Abstract Predicting future trends of Web events can help significantly improve the quality of Web services, e.g., improving the user satisfaction of news websites. Existing approaches in this regard are based mainly on temporal patterns mined with the assumption that enough temporal data is available on hand. However, most Web events do not have a long lifecycle, but a burst property, which drastically

    更新日期:2020-04-14
  • A deep-learning model for urban traffic flow prediction with traffic events mined from twitter
    World Wide Web (IF 2.892) Pub Date : 2020-03-14
    Aniekan Essien, Ilias Petrounias, Pedro Sampaio, Sandra Sampaio

    Abstract Short-term traffic parameter forecasting is critical to modern urban traffic management and control systems. Predictive accuracy in data-driven traffic models is reduced when exposed to non-recurring or non-routine traffic events, such as accidents, road closures, and extreme weather conditions. The analytical mining of data from social networks – specifically twitter – can improve urban traffic

    更新日期:2020-04-14
  • Decentralized Knowledge Acquisition for Mobile Internet Applications
    World Wide Web (IF 2.892) Pub Date : 2020-03-13
    Jing Jiang, Shaoxiong Ji, Guodong Long

    Abstract Mobile internet applications on smart phones dominate large portions of daily life for many people. Conventional machine learning-based knowledge acquisition methods collect users’ data in a centralized server, then train an intelligent model, such as recommendation and prediction, using all the collected data. This knowledge acquisition method raises serious privacy concerns, and also violates

    更新日期:2020-04-14
  • An enhanced wildcard-based fuzzy searching scheme in encrypted databases
    World Wide Web (IF 2.892) Pub Date : 2020-03-13
    Jiaxun Hua, Yu Liu, He Chen, Xiuxia Tian, Cheqing Jin

    Abstract Under the overwhelming trend in Cloud Computing, Cloud Databases possessing high scalability / high availability / high parallel performance have become a prevalent paradigm of data outsourcing. In consideration of security and privacy, both individuals and enterprises prefer to outsource service data in encrypted form. Unfortunately, most encrypted databases cannot support such complicated

    更新日期:2020-04-14
  • Towards a smarter directional data aggregation in VANETs
    World Wide Web (IF 2.892) Pub Date : 2020-03-12
    Sabri Allani, Taoufik Yeferny, Richard Chbeir, Sadok Ben Yahia

    Abstract In the last decade, Vehicular Ad hoc NETworks (VANETs) have attracted researchers, automotive companies and public governments, as a new communication technology to improve the safety of transportation systems aiming at offering smooth driving and safer roads. In this respect, a new Traffic Information System (TIS) has benefited from VANET services. The ultimate goal of a TIS consists in properly

    更新日期:2020-04-14
  • Processing capability and QoE driven optimized computation offloading scheme in vehicular fog based F-RAN
    World Wide Web (IF 2.892) Pub Date : 2020-03-12
    Tianpeng Ye, Xiang Lin, Jun Wu, Gaolei Li, Jianhua Li

    Abstract The Fog Computing was proposed to extend the computing task to the network edge in lots of Internet of Things (IoT) scenario, such as Internet of Vehicle (IoV). However, the unbalanced data processing requirement caused by the uneven distribution of vehicles in time and space limits the service capability of IoV. To enhance the flexibility and data processing capability, we propose a hybrid

    更新日期:2020-04-14
  • Multi-view network embedding with node similarity ensemble
    World Wide Web (IF 2.892) Pub Date : 2020-03-12
    Weiwei Yuan, Kangya He, Chenyang Shi, Donghai Guan, Yuan Tian, Abdullah Al-Dhelaan, Mohammed Al-Dhelaan

    Abstract Node similarity is utilized as the most popular guidance for network embedding: nodes more similar in a network should still be more similar when mapping node information from a high-dimensional vector space to a low-dimensional vector space. Most existing methods preserve a single node similarity in the network embedding, which can merely preserve one-side network structural information.

    更新日期:2020-04-14
  • Exploring nonnegative and low-rank correlation for noise-resistant spectral clustering
    World Wide Web (IF 2.892) Pub Date : 2020-03-12
    Zheng Wang, Lin Zuo, Jing Ma, Si Chen, Jingjing Li, Zhao Kang, Lei Zhang

    Abstract Clustering has been extensively explored in pattern recognition and data mining in order to facilitate various applications. Due to the presence of data noise, traditional clustering approaches may become vulnerable and unreliable, thereby degrading clustering performance. In this paper, we propose a robust spectral clustering approach, termed Non-negative Low-rank Self-reconstruction (NLS)

    更新日期:2020-04-14
  • Medical treatment migration behavior prediction and recommendation based on health insurance data
    World Wide Web (IF 2.892) Pub Date : 2020-03-12
    Lin Cheng, Yuliang Shi, Kun Zhang

    Abstract How to accurately predict the future medical treatment behaviors of patients from the historical health insurance data has become an important research issue in healthcare. In this paper, an Attention-based Bidirectional Gated Recurrent Unit (AB-GRU) medical treatment migration prediction model is proposed to predict which hospital patients will go to in the future. The model considers the

    更新日期:2020-04-14
  • Leveraging citation influences for Modeling scientific documents
    World Wide Web (IF 2.892) Pub Date : 2020-03-11
    Yue Qian, Yu Liu, Xiujuan Xu, Quan Z. Sheng

    Abstract This paper studies a link-text algorithm to model scientific documents by citation influences, which is applied to document clustering and influence prediction. Most existing link-text algorithms ignore the different weights of citation influences that cited documents have on the corresponding citing document. In fact, citation influences reveal the latent structure of citation networks which

    更新日期:2020-04-14
  • High-performance docker integration scheme based on OpenStack
    World Wide Web (IF 2.892) Pub Date : 2020-03-07
    Sijie Yang, Xiaofeng Wang, Xiaoxue Wang, Lun An, Guizhu Zhang

    As an emerging technology in cloud computing Docker is becoming increasingly popular due to its high speed high efficiency and portability. The integration of Docker with OpenStack has been a hot topic in research and industrial areas e.g. as an emulation platform for evaluating cyberspace security technologies. This paper introduces a high-performance Docker integration scheme based on OpenStack that

    更新日期:2020-03-07
  • Link prediction of scientific collaboration networks based on information retrieval
    World Wide Web (IF 2.892) Pub Date : 2020-03-07
    Dmytro Lande, Minglei Fu, Wen Guo, Iryna Balagura, Ivan Gorbov, Hongbo Yang

    Link prediction plays an important role in scientific collaboration networks, and can favourably affect the organization of international scientific projects. In this paper, a meta-path computed prediction (MPCP) algorithm for link prediction among scientists and publications is presented. The MPCP algorithm is based on a heterogeneous information network model composed of authors and keywords in articles

    更新日期:2020-03-07
  • Learning social representations with deep autoencoder for recommender system
    World Wide Web (IF 2.892) Pub Date : 2020-03-07
    Yiteng Pan, Fazhi He, Haiping Yu

    With the development of online social media, it attracts increasingly attentions to utilize social information for recommender systems. Based on the intuition that users are influenced by their social friends, these methods are capable of addressing the data sparse problem and improving the performance of recommender systems. However, these methods model the influences between each pair of users independently

    更新日期:2020-03-07
  • Outsourced data integrity verification based on blockchain in untrusted environment
    World Wide Web (IF 2.892) Pub Date : 2020-03-04
    Kun Hao, Junchang Xin, Zhiqiong Wang, Guoren Wang

    Outsourced data, as the significant component of cloud service, has been widely used due to its convenience, low overhead, and high flexibility. To guarantee the integrity of outsourced data, data owner (DO) usually adopts a third party auditor (TPA) to execute the data integrity verification scheme. However, during the verification process, DO cannot fully confirm the reliability of the TPA, and handing

    更新日期:2020-03-04
  • Mode decomposition based deep learning model for multi-section traffic prediction
    World Wide Web (IF 2.892) Pub Date : 2020-03-03
    Khouanetheva Pholsena, Li Pan, Zhenpeng Zheng

    Road traffic prediction plays a vital role in real-time traffic management of an intelligent transportation system (ITS). Many prediction models achieve fine results. However, most ignore the intrinsic characteristics of traffic parameter data and do not consider the spatiotemporal effects of road sections, which can reflect the situation of all road traffic. Therefore, multi-section traffic prediction

    更新日期:2020-03-03
  • Geographical address representation learning for address matching
    World Wide Web (IF 2.892) Pub Date : 2020-02-28
    Shuangli Shan, Zhixu Li, Qiang Yang, An Liu, Lei Zhao, Guanfeng Liu, Zhigang Chen

    Address matching is a crucial task in various location-based businesses like take-out services and express delivery, which aims at identifying addresses referring to the same location in address databases. It is a challenging one due to various possible ways to express the address of a location, especially in Chinese. Traditional address matching approaches relying on string similarities and learning

    更新日期:2020-02-28
  • User experience-driven secure task assignment in spatial crowdsourcing
    World Wide Web (IF 2.892) Pub Date : 2020-02-28
    Wei Peng, An Liu, Zhixu Li, Guanfeng Liu, Qing Li

    With the ubiquity of mobile devices and wireless networks, Spatial Crowdsourcing (SC) has earned considerable importance and attention as a new strategy of problem-solving. Tasks in SC have location constraints and workers need to move to certain locations to perform them. Current studies mainly focus on maximizing the benefits of the SC platform. However, user average waiting time, which is an important

    更新日期:2020-02-28
  • Web service QoS prediction: when collaborative filtering meets data fluctuating in big-range
    World Wide Web (IF 2.892) Pub Date : 2020-02-19
    Zhen Chen, Limin Shen, Feng Li, Dianlong You, Jean Pepe Buanga Mapetu

    Service recommendation aims to help users to find the most suitable Web services based on their quality of service (QoS) preferences instead of searching through extensive volume of Web services using search engine manually. Accurate unknown QoS rating prediction is one of the key challenges in the analysis of service recommendation. Collaborative filtering (CF) is a well-known recommendation method

    更新日期:2020-02-19
  • Automatic Web service composition driven by keyword query
    World Wide Web (IF 2.892) Pub Date : 2020-02-07
    Dongjin Yu, Lei Zhang, Chengfei Liu, Rui Zhou, Dengwei Xu

    Service-based systems (SBSs) reuse existing loosely coupled Web services to provide value-added composite ones, which brings about much flexibility when the business changes frequently. The advent of automatic Web service composition technology allows system designers to quickly build SBSs without having to manually create process models. Despite the large number of strategies proposed so far, most

    更新日期:2020-02-07
  • Survey on user location prediction based on geo-social networking data
    World Wide Web (IF 2.892) Pub Date : 2020-01-31
    Shuai Xu, Xiaoming Fu, Jiuxin Cao, Bo Liu, Zhixiao Wang

    With the popularity of smart mobile terminals and advances in wireless communication and positioning technologies, Geo-Social Networks (GSNs), which combine location awareness and social service functions, have become increasingly prevalent. The increasing amount of user and location information in GSNs makes the information overload phenomenon more and more serious. Although massive user-generated

    更新日期:2020-01-31
  • iLinker: a novel approach for issue knowledge acquisition in GitHub projects
    World Wide Web (IF 2.892) Pub Date : 2020-01-27
    Yang Zhang, Yiwen Wu, Tao Wang, Huaimin Wang

    Social coding facilitates the sharing of knowledge in GitHub projects. In particular, issue reports, as an important knowledge in the software development, usually contain relevant information, and can thus be shared and linked in the developers’ discussion to aid the issue resolution. Linking issues to potentially related issues, i.e. issue knowledge acquisition, would provide developers with more

    更新日期:2020-01-27
  • Robust SVM with adaptive graph learning
    World Wide Web (IF 2.892) Pub Date : 2019-12-27
    Rongyao Hu, Xiaofeng Zhu, Yonghua Zhu, Jiangzhang Gan

    Support Vector Machine (SVM) has been widely applied in real application due to its efficient performance in the classification task so that a large number of SVM methods have been proposed. In this paper, we present a novel SVM method by taking the dynamic graph learning and the self-paced learning into account. To do this, we propose utilizing self-paced learning to assign important samples with

    更新日期:2019-12-27
  • Query-based unsupervised learning for improving social media search
    World Wide Web (IF 2.892) Pub Date : 2019-11-27
    Khaled Albishre, Yuefeng Li, Yue Xu, Wei Huang

    In the current information era over the internet, social media has become one of the essential information sources for users. While the text is the primary information representation, finding relevant information is a challenging mission for researchers due to its nature (e.g., short length, sparseness). Acquiring high-quality search results from massive data, such as social media needs a set of representative

    更新日期:2019-11-27
  • Author Correction: A lightweight and cost effective edge intelligence architecture based on containerization technology
    World Wide Web (IF 2.892) Pub Date : 2019-11-22
    Mabrook Al-Rakhami, Abdu Gumaei, Mohammed Alsahli, Mohammad Mehedi Hassan, Atif Alamri, Antonio Guerrieri, Giancarlo Fortino

    The original version of this article unfortunately contained a mistake. In the originally published version, the acknowledgments information is missing. The article’s acknowledgments information is provided below.

    更新日期:2019-11-22
  • Recommender system for marketing optimization
    World Wide Web (IF 2.892) Pub Date : 2019-11-18
    Wei Deng, Yong Shi, Zhengxin Chen, Wikil Kwak, Huimin Tang

    Most of existing e-commerce recommender systems have been designed to recommend the right products to users, based on the history of previous users’ individual transaction records. The real application scenarios of recommendation also have different requirements. From the customer point of view, many users visit the websites anonymously, so a practical way to provide anonymous recommendation is needed

    更新日期:2019-11-18
  • A Framework for Discovering Health Disparities among Cohorts in an Influenza Epidemic.
    World Wide Web (IF 2.892) Pub Date : 2019-11-30
    Lijing Wang,Jiangzhuo Chen,Achla Marathe

    Infectious diseases such as Influenza and Ebola pose a serious threat to everyone but certain demographics and cohorts face a higher risk of infection than others. This research provides a computational framework for studying health disparities among cohorts based on individual level features, such as age, gender, income, etc. We apply this framework to find health disparities among subpopulations

    更新日期:2019-11-01
  • Group sparse reduced rank regression for neuroimaging genetic study.
    World Wide Web (IF 2.892) Pub Date : 2019-10-15
    Xiaofeng Zhu,Heung-Il Suk,Dinggang Shen

    The neuroimaging genetic study usually needs to deal with high dimensionality of both brain imaging data and genetic data, so that often resulting in the issue of curse of dimensionality. In this paper, we propose a group sparse reduced rank regression model to take the relations of both the phenotypes and the genotypes for the neuroimaging genetic study. Specifically, we propose designing a graph

    更新日期:2019-11-01
  • From ideal to reality: segmentation, annotation, and recommendation, the vital trajectory of intelligent micro learning
    World Wide Web (IF 2.892) Pub Date : 2019-10-23
    Jiayin Lin, Geng Sun, Tingru Cui, Jun Shen, Dongming Xu, Ghassan Beydoun, Ping Yu, David Pritchard, Li Li, Shiping Chen

    The soaring development of Web technologies and mobile devices has blurred time-space boundaries of people’s daily activities. Such development together with the life-long learning requirement give birth to a new learning style, micro learning. Micro learning aims to effectively utilize learners’ fragmented time to carry out personalized learning activities through online education resources. The whole

    更新日期:2019-10-23
  • End-to-End latent-variable task-oriented dialogue system with exact log-likelihood optimization
    World Wide Web (IF 2.892) Pub Date : 2019-06-07
    Haotian Xu, Haiyun Peng, Haoran Xie, Erik Cambria, Liuyang Zhou, Weiguo Zheng

    We propose an end-to-end dialogue model based on a hierarchical encoder-decoder, which employed a discrete latent variable to learn underlying dialogue intentions. The system is able to model the structure of utterances dominated by statistics of the language and the dependencies among utterances in dialogues without manual dialogue state design. We argue that the latent discrete variable interprets

    更新日期:2019-06-07
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