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  • ELIS++: a shapelet learning approach for accurate and efficient time series classification
    World Wide Web (IF 2.892) Pub Date : 2021-01-09
    Hanbo Zhang, Peng Wang, Zicheng Fang, Zeyu Wang, Wei Wang

    In recent years, time series classification with shapelets, due to the high accuracy and good interpretability, has attracted considerable interests. These approaches extract or learn shapelets from the training time series. Although they can achieve higher accuracy than other approaches, there still confront some challenges. First, they may suffer from low accuracy in the case of small training dataset

    更新日期:2021-01-10
  • DDoS attacks in IoT networks: a comprehensive systematic literature review
    World Wide Web (IF 2.892) Pub Date : 2021-01-06
    Yahya Al-Hadhrami, Farookh Khadeer Hussain

    The Internet of Things (IoT) is a rapidly emerging technology in the consumer and industrial market. This technology has the potential to radically transform the consumer experience, as it will change our daily scenes, starting from the way we drink coffee to how smart objects interact with industrial applications. Such rapid development and deployment face multifarious challenges, including the sheer

    更新日期:2021-01-07
  • Core decomposition and maintenance in weighted graph
    World Wide Web (IF 2.892) Pub Date : 2021-01-05
    Wei Zhou, Hong Huang, Qiang-Sheng Hua, Dongxiao Yu, Hai Jin, Xiaoming Fu

    Coreness is an important index to reflect the cohesiveness of a graph. The problems of core computation in static graphs and core update in dynamic graphs, known as the core decomposition and core maintenance problems respectively, have been extensively studied in previous work. However, most of these work focus on unweighted graphs. Considering that graphs are weighted in a lot of realistic applications

    更新日期:2021-01-05
  • Parallel algorithms for parameter-free structural diversity search on graphs
    World Wide Web (IF 2.892) Pub Date : 2020-11-20
    Jinbin Huang, Xin Huang, Yuanyuan Zhu, Jianliang Xu

    Structural diversity of a user in a social network is the number of social contexts in his/her contact neighborhood. The problem of structural diversity search is to find the top-k vertices with the largest structural diversity in a graph. However, when identifying distinct social contexts, existing structural diversity models (e.g., t-sized component, t-core, and t-brace) are sensitive to an input

    更新日期:2020-11-21
  • A survey of typical attributed graph queries
    World Wide Web (IF 2.892) Pub Date : 2020-11-20
    Yanhao Wang, Yuchen Li, Ju Fan, Chang Ye, Mingke Chai

    Graphs are commonly used for representing complex structures such as social relationships, biological interactions, and knowledge bases. In many scenarios, graphs not only represent topological relationships but also store the attributes that denote the semantics associated with their vertices and edges, known as attributed graphs. Attributed graphs can meet demands for a wide range of applications

    更新日期:2020-11-21
  • Handling conditional queries and data storage on Hyperledger Fabric efficiently
    World Wide Web (IF 2.892) Pub Date : 2020-11-14
    Tianlu Yan, Wei Chen, Pengpeng Zhao, Zhixu Li, An Liu, Lei Zhao

    As a popular consortium blockchain platform, Hyperledger Fabric has received increasing attention recently. When executing transactions on such platform, it usually costs a lot of time and hardly to achieve high efficiency. Although efficiently handling transactions can be leveraged to support various use-cases, it presents significant challenges as data on Hyperledger Fabric is organized on file-system

    更新日期:2020-11-15
  • Solutions for concurrency conflict problem on Hyperledger Fabric
    World Wide Web (IF 2.892) Pub Date : 2020-11-14
    Lu Xu, Wei Chen, Zhixu Li, Jiajie Xu, An Liu, Lei Zhao

    A Hyperledger Fabric is a popular permissioned blockchain platform and has great commercial application prospects. However, the limited transaction throughput of Hyperledger Fabric hampers its performance, especially when transactions with concurrency conflicts are initiated. In this paper, we focus on transactions with concurrency conflicts and propose solutions to optimize the performance of Hyperledger

    更新日期:2020-11-15
  • Assessing the authenticity of subjective information in the blockchain: a survey and open issues
    World Wide Web (IF 2.892) Pub Date : 2020-11-12
    Hang Thanh Bui, Omar Khadeer Hussain, Morteza Saberi, Farookh Hussain

    Blockchain, with its ever-increasing maturity and popularity, is being used in many different applied computing domains. To document the advancements made, researchers have conducted surveys on blockchain from many different viewpoints. However, one perspective which is missing from such surveys is how to assess the authenticity of subjective information and consider this in the processing of blockchain

    更新日期:2020-11-12
  • Open-world knowledge graph completion with multiple interaction attention
    World Wide Web (IF 2.892) Pub Date : 2020-10-28
    Lei Niu, Chenpeng Fu, Qiang Yang, Zhixu Li, Zhigang Chen, Qingsheng Liu, Kai Zheng

    Knowledge Graph Completion (KGC) aims at complementing missing relationships between entities in a Knowledge Graph (KG). While closed-world KGC approaches utilizing the knowledge within KG could only complement very limited number of missing relations, more and more approaches tend to get knowledge from open-world resources such as online encyclopedias and newswire corpus. For instance, a recent proposed

    更新日期:2020-10-30
  • Backup gateways for IoT mesh network using order-k hops Voronoi diagram
    World Wide Web (IF 2.892) Pub Date : 2020-10-27
    Kiki Adhinugraha, Wenny Rahayu, Takahiro Hara, David Taniar

    Mesh network is a common topology in deploying Edge/Fog computing in IoT due to its robustness, expandability and reliability. In the Mesh topology, gateways are the key role for the entire networks to communicate with the clouds. In order to ensure network availability in a failover scenario, a router must always have backup gateways to maintain mesh robustness during primary gateway failover. Order-k

    更新日期:2020-10-30
  • Deep fusion of multimodal features for social media retweet time prediction
    World Wide Web (IF 2.892) Pub Date : 2020-10-24
    Hui Yin, Shuiqiao Yang, Xiangyu Song, Wei Liu, Jianxin Li

    The popularity of various social media platforms (e.g., Twitter, Facebook, Instagram, and Weibo) has led to the generation of millions of micro-blogs each day. Retweet (message forwarding function) is considered to be one of the most effective behavior for information propagation on social networks. The task of retweet behavior prediction has received much attention in recent years, such as modelling

    更新日期:2020-10-30
  • Leveraging pointwise prediction with learning to rank for top-N recommendation
    World Wide Web (IF 2.892) Pub Date : 2020-10-23
    Nengjun Zhu, Jian Cao, Xinjiang Lu, Qi Gu

    Pointwise prediction and Learning to Rank (L2R) are two hot strategies to model user preference in recommender systems. Currently, these two types of approaches are often considered independently, and most existing efforts utilize them separately. Unfortunately, pointwise prediction tends to cause the problem of overfitting, while L2R is more prone to higher variance. On the other hand, the advantages

    更新日期:2020-10-30
  • LoG: a locally-global model for entity disambiguation
    World Wide Web (IF 2.892) Pub Date : 2020-10-22
    Kexuan Xin, Wen Hua, Yu Liu, Xiaofang Zhou

    Entity disambiguation (ED) aims to link textual mentions in a document to the correct named entities in a knowledge base (KB). Although global ED models usually outperform local models by collectively linking mentions based on the topical coherence assumption, they may still incur incorrect entity assignment when a document contains multiple topics. Therefore, we propose a Locally-Global model (LoG)

    更新日期:2020-10-30
  • Reverse Approximate Nearest Neighbor Queries on Road Network
    World Wide Web (IF 2.892) Pub Date : 2020-10-14
    Xinyu Li, Arif Hidayat, David Taniar, Muhammad Aamir Cheema

    Reverse k Nearest Neighbor (RkNN) queries retrieve all objects that consider the query as one of their k most influential objects. Given a set of user U, a set of facilities F and a value k, a facility f is said to be influential to a user u if f is one of the k closest facilities to u. As a complement of RkNN query, Reverse Approximate Nearest Neighbor (RANN) query considers relaxed definition of

    更新日期:2020-10-15
  • An efficient multidimensional L ∞ $L_{\infty }$ wavelet method and its application to approximate query processing
    World Wide Web (IF 2.892) Pub Date : 2020-10-10
    Xueyan Guo, Tongliang Li, Xiaoyun Li, Huanyu Zhao, Suzhen Wang, Chaoyi Pang

    Approximate query processing (AQP) has been an effective approach for real-time and online query processing for today’s query systems. It provides approximate but fast query results to users. In wavelet based AQP, queries are executed against the wavelet synopsis which is a lossy, compressed representation of the original data returned by a specific wavelet method. Wavelet synopsis optimized for \(L_{\infty

    更新日期:2020-10-11
  • Using context information to enhance simple question answering
    World Wide Web (IF 2.892) Pub Date : 2020-10-01
    Lin Li, Mengjing Zhang, Zhaohui Chao, Jianwen Xiang

    With the rapid development of knowledge bases (KBs), question answering (QA) based on KBs has become a hot research issue. The KB-QA technology can be divided into two technical routes: (1) symbol based representations, such as traditional semantic parsing, and (2) distribution based embedding. With the emergence of deep learning, the development of NLP has greatly promoted. The effect of KB-QA can

    更新日期:2020-10-02
  • A multi-view attention-based deep learning system for online deviant content detection
    World Wide Web (IF 2.892) Pub Date : 2020-09-30
    Yunji Liang, Bin Guo, Zhiwen Yu, Xiaolong Zheng, Zhu Wang, Lei Tang

    With the exponential growth of user-generated content, policies and guidelines are not always enforced in social media, resulting in the prevalence of deviant content violating policies and guidelines. The adverse effects of deviant content are devastating and far-reaching. However, the detection of deviant content from sparse and imbalanced textual data is challenging, as a large number of stakeholders

    更新日期:2020-09-30
  • Closed sequential pattern mining for sitemap generation
    World Wide Web (IF 2.892) Pub Date : 2020-09-27
    Michelangelo Ceci, Pasqua Fabiana Lanotte

    A sitemap represents an explicit specification of the design concept and knowledge organization of a website and is therefore considered as the website’s basic ontology. It not only presents the main usage flows for users, but also hierarchically organizes concepts of the website. Typically, sitemaps are defined by webmasters in the very early stages of the website design. However, during their life

    更新日期:2020-09-28
  • Robust rumor blocking problem with uncertain rumor sources in social networks
    World Wide Web (IF 2.892) Pub Date : 2020-09-27
    Jianming Zhu, Smita Ghosh, Weili Wu

    Rumormongers spread negative information throughout the social network, which may even lead to panic or unrest. Rumor should be blocked by spreading positive information from several protector nodes in the network. Users will not be influenced if they receive the positive information ahead of negative one. In many cases, network manager or government may not know the exact positions where rumor will

    更新日期:2020-09-28
  • Firmware code instrumentation technology for internet of things-based services
    World Wide Web (IF 2.892) Pub Date : 2020-09-26
    Chen Chen, Jinxin Ma, Tao Qi, Baojiang Cui, Weikong Qi, Zhaolei Zhang, Peng Sun

    With the rapid development of electronic and information technology, Internet of Things (IoT) devices have become extensively utilised in various fields. Increasing attention has been paid to the performance and security analysis of IoT-based services. Dynamic instrumentation is a common process in software analysis for acquiring runtime information. However, due to the limited software and hardware

    更新日期:2020-09-26
  • A general strategy for researches on Chinese “的(de)” structure based on neural network
    World Wide Web (IF 2.892) Pub Date : 2020-09-13
    Bingqing Shi, Weiguang Qu, Rubing Dai, Bin Li, Xiaohui Yan, Junsheng Zhou, Yanhui Gu, Ge Xu

    Noun phrases reflect people’s understanding of the world entities and play an important role in people’s language system, conceptual system and application system. With the Chinese “的(de)” structure, attributive noun phrases of the combined type can accommodate more words and syntactic structures, resulting in rich levels and complex semantic structures in Chinese sentences. Moreover, the Chinese elliptical

    更新日期:2020-09-14
  • Improving biterm topic model with word embeddings
    World Wide Web (IF 2.892) Pub Date : 2020-09-08
    Jiajia Huang, Min Peng, Pengwei Li, Zhiwei Hu, Chao Xu

    As one of the fundamental information extraction methods, topic model has been widely used in text clustering, information recommendation and other text analysis tasks. Conventional topic models mainly utilize word co-occurrence information in texts for topic inference. However, it is usually hard to extract a group of words that are semantically coherent and have competent representation ability when

    更新日期:2020-09-08
  • Temporal knowledge extraction from large-scale text corpus
    World Wide Web (IF 2.892) Pub Date : 2020-09-02
    Yu Liu, Wen Hua, Xiaofang Zhou

    Knowledge, in practice, is time-variant and many relations are only valid for a certain period of time. This phenomenon highlights the importance of harvesting temporal-aware knowledge, i.e., the relational facts coupled with their valid temporal interval. Inspired by pattern-based information extraction systems, we resort to temporal patterns to extract time-aware knowledge from free text. However

    更新日期:2020-09-02
  • Existence identifications of unobserved paths in graph-based social networks
    World Wide Web (IF 2.892) Pub Date : 2020-09-01
    Huan Wang, Qiufen Ni, Jiali Wang, Hao Li, Fuchuan Ni, Hao Wang, Liping Yan

    In recent years, social networks have surged in popularity as one of the main applications of the Internet. One key aspect of social network research is exploring important unobserved network information which is not explicitly represented. This study first introduces a new path identification problem to identify the existences of unobserved paths between nodes. Given a partial social network structure

    更新日期:2020-09-02
  • User interest-based recommender system for image-sharing social media
    World Wide Web (IF 2.892) Pub Date : 2020-08-22
    Kunyoung Kim, Jongmo Kim, Minhwan Kim, Mye Sohn

    Nowadays, many people use social media to communicate with others, share their interests and obtain information. As the performance of the embedded cameras on mobile phones improve, image-sharing social media became a popular tool for people to communicate with others and share their interests, which yields vast amount of data related to the users’ interests. However, only few studies pay attention

    更新日期:2020-08-22
  • Application of fuzzy logic for IoT node elimination and selection in opportunistic networks: performance evaluation of two fuzzy-based systems
    World Wide Web (IF 2.892) Pub Date : 2020-08-17
    Miralda Cuka, Donald Elmazi, Makoto Ikeda, Keita Matsuo, Leonard Barolli, Makoto Takizawa

    Opportunistic Networks (OppNets) are a sub-class of DTN, designed as a specialized ad hoc network suitable for applications such as emergency responses. Unlike traditional networks, in OppNets communication opportunities are intermittent, so an end-to-end path between the source and the destination may never exist. Existing networks have already brought connectivity to a broad range of devices, such

    更新日期:2020-08-18
  • RLINK: Deep reinforcement learning for user identity linkage
    World Wide Web (IF 2.892) Pub Date : 2020-08-07
    Xiaoxue Li, Yanan Cao, Qian Li, Yanmin Shang, Yangxi Li, Yanbing Liu, Guandong Xu

    User identity linkage is a task of recognizing the identities of the same user across different social networks (SN). Previous works tackle this problem via estimating the pairwise similarity between identities from different SN, predicting the label of identity pairs or selecting the most relevant identity pair based on the similarity scores. However, most of these methods fail to utilize the results

    更新日期:2020-08-08
  • 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
  • Extracting representative user subset of social networks towards user characteristics and topological features
    World Wide Web (IF 2.892) Pub Date : 2020-06-30
    Yiming Zhou; Yuehui Han; An Liu; Zhixu Li; Hongzhi Yin; Wei Chen; Lei Zhao

    Extracting a subset of representative users from the original set in social networks plays a critical role in Social Network Analysis. In existing studies, some researchers focus on preserving users’ characteristics when sampling representative users, while others pay attention to preserving the topology structure. However, both users’ characteristics and the network topology contain abundant information

    更新日期:2020-06-30
  • Hybrid graph convolutional networks with multi-head attention for location recommendation
    World Wide Web (IF 2.892) Pub Date : 2020-06-23
    Ting Zhong, Shengming Zhang, Fan Zhou, Kunpeng Zhang, Goce Trajcevski, Jin Wu

    Recommending yet-unvisited points of interest (POIs) which may be of interest to users is one of the fundamental applications in location-based social networks. It mainly replies on the understanding of users, POIs, and their interactions. Previous studies either develop matrix factorization-based approaches or utilize deep learning frameworks to learn better representation of users and POIs in order

    更新日期:2020-06-23
  • 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:2020-04-17
  • 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
  • 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

    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

    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 as

    更新日期:2020-04-11
  • 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

    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 knowledge

    更新日期:2020-04-08
  • 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

    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 sensitive

    更新日期:2020-04-01
  • 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

    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 of

    更新日期:2020-03-31
  • 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

    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 cloud compliance

    更新日期:2020-03-31
  • 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

    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 or limited

    更新日期:2020-03-27
  • 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

    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 measures

    更新日期:2020-03-26
  • 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

    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 sets in classification

    更新日期:2020-03-20
  • 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

    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 of social

    更新日期:2020-03-19
  • 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

    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 reduces

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

    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 the

    更新日期:2020-03-13
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