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• Introduction Ranking-Based Clustering Classification of Heterogeneous Information Networks Meta-Path-Based Similarity Search Meta-Path-Based Relationship Prediction Relation Strength-Aware Clustering with Incomplete Attributes User-Guided Clustering via Meta-Path Selection Research Frontiers.
• (source: Nielsen Book Data)

Real-world physical and abstract data objects are interconnected, forming gigantic, interconnected networks. By structuring these data objects and interactions between these objects into multiple types, such networks become semi-structured heterogeneous information networks. Most real-world applications that handle big data, including interconnected social media and social networks, scientific, engineering, or medical information systems, online e-commerce systems, and most database systems, can be structured into heterogeneous information networks. Therefore, effective analysis of large-scale heterogeneous information networks poses an interesting but critical challenge. In this book, we investigate the principles and methodologies of mining heterogeneous information networks. Departing from many existing network models that view interconnected data as homogeneous graphs or networks, our semi-structured heterogeneous information network model leverages the rich semantics of typed nodes and links in a network and uncovers surprisingly rich knowledge from the network. This semi-structured heterogeneous network modeling leads to a series of new principles and powerful methodologies for mining interconnected data, including: (1) rank-based clustering and classification; (2) meta-path-based similarity search and mining; (3) relation strength-aware mining, and many other potential developments. This book introduces this new research frontier and points out some promising research directions.
(source: Nielsen Book Data)

• Introduction Ranking-Based Clustering Classification of Heterogeneous Information Networks Meta-Path-Based Similarity Search Meta-Path-Based Relationship Prediction Relation Strength-Aware Clustering with Incomplete Attributes User-Guided Clustering via Meta-Path Selection Research Frontiers.
• (source: Nielsen Book Data)

Real-world physical and abstract data objects are interconnected, forming gigantic, interconnected networks. By structuring these data objects and interactions between these objects into multiple types, such networks become semi-structured heterogeneous information networks. Most real-world applications that handle big data, including interconnected social media and social networks, scientific, engineering, or medical information systems, online e-commerce systems, and most database systems, can be structured into heterogeneous information networks. Therefore, effective analysis of large-scale heterogeneous information networks poses an interesting but critical challenge. In this book, we investigate the principles and methodologies of mining heterogeneous information networks. Departing from many existing network models that view interconnected data as homogeneous graphs or networks, our semi-structured heterogeneous information network model leverages the rich semantics of typed nodes and links in a network and uncovers surprisingly rich knowledge from the network. This semi-structured heterogeneous network modeling leads to a series of new principles and powerful methodologies for mining interconnected data, including: (1) rank-based clustering and classification; (2) meta-path-based similarity search and mining; (3) relation strength-aware mining, and many other potential developments. This book introduces this new research frontier and points out some promising research directions.
(source: Nielsen Book Data)

• [I]. BlockChain and Crowdsourcing: GroExpert: A Novel Group-Aware Experts Identification Approach in Crowdsourcing / Qianli Xing, Weiliang Zhao, Jian Yang, Jia Wu, Qi Wang, and Mei Wang
• Detecting Fraudulent Accounts on Blockchain: A Supervised Approach / Michał Ostapowicz and Kamil Żbikowski
• Locking Mechanism for Concurrency Conflicts on Hyperledger Fabric / Lu Xu, Wei Chen, Zhixu Li, Jiajie Xu, An Liu, and Lei Zhao
• Handling Conditional Queries on Hyperledger Fabric Efficiently / Tianlu Yan, Wei Chen, Pengpeng Zhao, Zhixu Li, An Liu, and Lei Zhao.

• [II]. Machine Learning: Learning to Fuse Multiple Semantic Aspects from Rich Texts for Stock Price Prediction / Ning Tang, Yanyan Shen, and Junjie Yao
• Transfer Learning via Feature Selection Based Nonnegative Matrix Factorization / Thirunavukarasu Balasubramaniam, Richi Nayak, and Chau Yuen
• Learning Restricted Deterministic Regular Expressions with Counting / Xiaofan Wang and Haiming Chen
• Generating Adversarial Examples by Adversarial Networks for Semi-supervised Learning / Yun Ma, Xudong Mao, Yangbin Chen, and Qing Li.

• [III]. Deep Learning: Dual Path Convolutional Neural Network for Student Performance Prediction / Yuling Ma, Jian Zong, Chaoran Cui, Chunyun Zhang, Qizheng Yang, and Yilong Yin
• A Case Based Deep Neural Network Interpretability Framework and Its User Study / Rimmal Nadeem, Huijun Wu, Hye-young Paik, and Chen Wang
• Personalized Book Recommendation Based on a Deep Learning Model and Metadata / Yiu-Kai Ng and Urim Jung
• DINRec: Deep Interest Network Based API Recommendation Approach for Mashup Creation / Yong Xiao, Jianxun Liu, Rong Hu, Buqing Cao, and Yingcheng Cao.

• [IV]. Recommender System: Co-purchaser Recommendation Based on Network Embedding / Jihong Chen, Wei Chen, Jinjing Huang, Jinhua Fang, Zhixu Li, An Liu, and Lei Zhao
• Community-Based Recommendations on Twitter: Avoiding the Filter Bubble / Quentin Grossetti, Cédric du Mouza, and Nicolas Travers
• Memory-Augmented Attention Network for Sequential Recommendation / Multi-head Attentive Social Recommendation / Xu Luo, Chaofeng Sha, Zijing Tan, and Junyu Niu
• CPL: A Combined Framework of Pointwise Prediction and Learning to Rank for top-N Recommendations with Implicit Feedback / Nengjun Zhu and Jian Cao .

• [V]. Data mining: RTIM: A Real-Time Influence Maximization Strategy / David Dupuis, Cédric du Mouza, Nicolas Travers, and Gaël Chareyron
• LSCMiner: Efficient Low Support Closed Itemsets Mining / Yifeng Lu, Florian Richter, and Thomas Seidl
• Pattern Filtering Attention for Distant Supervised Relation Extraction via Online Clustering / Min Peng, Qingwen Liao, Weilong Hu, Gang Tian, Hua Wang, and YanChun Zhang
• Adaptive Rule Adaptation in Unstructured and Dynamic Environments / Alireza Tabebordbar, Amin Beheshti, Boualem Benatallah, and Moshe Chai Barukh
• Shadowed Authorization Policies -- A Disaster Waiting to Happen? / Ehtesham Zahoor, Uzma Bibi, and Olivier Perrin.

• [VI]. Web-Based Applications: A Dynamic Decision-Making Method Based on Ensemble Methods for Complex Unbalanced Data / Dong Chen, Xiao-Jun Wang, and Bin Wang
• Collaborative Wireframing for Model-Driven Web Engineering / Peter de Lange, Petru Nicolaescu, Mario Rosenstengel, and Ralf Klamma
• Handling Disagreement in Ontologies-Based Reasoning via Argumentation / Said Jabbour, Yue Ma, and Badran Raddaoui
• A Cost-Efficient Multi-cloud Orchestrator for Benchmarking Containerized Web-Applications / Devki Nandan Jha, Zhenyu Wen, Yinhao Li, Michael Nee, Maciej Koutny, and Rajiv Ranjan
• Highlighting Weasel Sentences for Promoting Critical Information Seeking on the Web / Fumiaki Saito, Yoshiyuki Shoji, and Yusuke Yamamoto
• Generating an Evolving Skills Network from Job Adverts for High-Demand Skillset Discovery / Elisa Margareth Sibarani and Simon Scerri
• Picture News Collection: A Dataset for Automatic Picture News Thumbnail Selection / Yi-Kun Tang, Heyan Huang, Xuewen Shi, and Xian-Ling Mao
• A Graph-Based Approach to Explore Relationship Between Hashtags and Images / Zhiqiang Zhong, Yang Zhang, and Jun Pang.

• [VII]. Entity Linkage and Disambiguation: RDF Graph Anonymization Robust to Data Linkage / Remy Delanaux, Angela Bonifati, Marie-Christine Rousset, and Romuald Thion
• WebEL: Improving Entity Linking with Extra Web Contexts / Yiting Wang, Zhixu Li, Qiang Yang, Zhigang Chen, An Liu, Guanfeng Liu, and Lei Zhao
• Entity Disambiguation Based on Parse Tree Neighbours on Graph Attention Network / Kexuan Xin, Wen Hua, Yu Liu, and Xiaofang Zhou
• Bibliographic Name Disambiguation with Graph Convolutional Network / Hao Yan, Hao Peng, Chen Li, Jianxin Li, and Lihong Wang.

• [VIII]. Graph Learning: Semi-supervised Graph Embedding for Multi-label Graph Node Classification / Kaisheng Gao, Jing Zhang, and Cangqi Zhou
• Structural Role Enhanced Attributed Network Embedding / Zhao Li, Xin Wang, Jianxin Li, and Qingpeng Zhang
• Context-Aware Temporal Knowledge Graph Embedding / Yu Liu, Wen Hua, Kexuan Xin, and Xiaofang Zhou
• Interaction Graph Neural Network for News Recommendation / Yongye Qian, Pengpeng Zhao, Zhixu Li, Junhua Fang, Lei Zhao, Victor S. Sheng, and Zhiming Cui.

• [IX]. Knowledge Graphs: Gated Relational Graph Neural Network for Semi-supervised Learning on Knowledge Graphs / Yuyan Chen, Lei Zou, and Zongyue Qin
• Multiple Interaction Attention Model for Open-World Knowledge Graph Completion / Chenpeng Fu, Zhixu Li, Qiang Yang, Zhigang Chen, Junhua Fang, Pengpeng Zhao, and Jiajie Xu
• OntoDS: An Ontology-Aware Distributed Storage Scheme for RDF Graphs / Baozhu Liu, Xin Wang, Yajun Yang, and Yunpeng Chai
• Learning Relational Fractals for Deep Knowledge Graph Embedding in Online Social Networks / Ji Zhang, Leonard Tan, Xiaohui Tao, Dianwei Wang, Josh Jia-Ching Ying, and Xin Wang.

• [X]. Graph Mining: Parameter-Free Structural Diversity Search / Jinbin Huang, Xin Huang, Yuanyuan Zhu, and Jianliang Xu
• CoreCube: Core Decomposition in Multilayer Graphs / Boge Liu, Fan Zhang, Chen Zhang, Wenjie Zhang, and Xuemin Lin
• Computing Maximum Independent Sets over Large Sparse Graphs / Maram Alsahafy and Lijun Chang
• Fast Algorithms for Intimate-Core Group Search in Weighted Graphs / Longxu Sun, Xin Huang, Rong-Hua Li, and Jianliang Xu.

• [XI]. Text Mining: Unsupervised Ontology- and Sentiment-Aware Review Summarization / Nhat X. T. Le, Neal Young, and Vagelis Hristidis
• Enriching the Context: Methods of Improving the Non-contextual Assessment of Sentence Credibility / Aleksandra Nabożny, Bartłomiej Balcerzak, and Danijel Koržinek
• ConceptMap: A Conceptual Approach for Formulating User Preferences in Large Information Spaces / Alireza Tabebordbar, Amin Beheshti, and Boualem Benatallah
• Helpfulness Prediction for Online Reviews with Explicit Content-Rating Interaction / Jiahua Du, Jia Rong, Hua Wang, and Yanchun Zhang.

This book constitutes the proceedings of the 20th International Conference on Web Information Systems Engineering, WISE 2019, held in Hong Kong, China, in November 2019. The 50 full papers presented were carefully reviewed and selected from 211 submissions. The papers are organized in the following topical sections: blockchain and crowdsourcing; machine learning; deep learning; recommender systems, data mining; web-based applications; entity linkage and disambiguation; graph learning; knowledge graphs; graph mining; and text mining. -- Provided by publisher.

• Graph and Social Network
• An Influence Field Perspective on Predicting User's Retweeting Behavior
• Realizing Impact Sourcing by Adaptive Gold Questions: A Socially Responsible Measure for Workers' Trustworthiness
• A Coalition Formation Game Theory-Based Approach for Detecting Communities in Multi-relational Networks
• Individual Influence Maximization via Link Recommendation
• Community Detection Based on Minimum-Cut Graph Partitioning
• Coherent Topic Hierarchy: A Strategy for Topic Evolutionary Analysis on Microblog Feeds
• Age Detection for Chinese Users in Weibo
• Batch Mode Active Learning for Networked Data With Optimal Subset Selection
• Information and Knowledge
• A Question Answering System Built on Domain Knowledge Base
• Fast and Accurate Computation of Role Similarity via Vertex Centrality
• Multimodal-Based Supervised Learning for Image Search Reranking
• Novel Word Features for Keyword Extraction
• A Multi-round Global Performance Evaluation Method for Interactive Image Retrieval
• Resorting Relevance Evidences to Cumulative Citation Recommendation for Knowledge Base Acceleration
• Relevance Search on Signed Heterogeneous Information Network Based on Meta-path Factorization
• Improving the Effectiveness of Keyword Search in Databases Using Query Logs
• cluTM: Content and Link Integrated Topic Model on Heterogeneous Information Networks
• Recommender Systems
• Learning to Recommend with User Generated Content
• Combining Positive and Negative Feedbacks with Factored Similarity Matrix for Recommender Systems
• Review Comment Analysis for Predicting Ratings
• Adaptive Temporal Model for IPTV Recommendation
• RPCV: Recommend Potential Customers to Vendors in Location-Based Social Network
• Mining Dependencies Considering Time Lag in Spatio-Temporal Traffic Data
• Location Semantics Protection Based on Bayesian Inference
• Big Data
• SALA: A Skew-Avoiding and Locality-Aware Algorithm for MapReduce-Based Join
• Energy-Proportional Query Processing on Database Clusters
• SparkRDF: In-Memory Distributed RDF Management Framework for Large-Scale Social Data
• Distributed Grid-Based K Nearest Neighbour Query Processing Over Moving Objects
• An Efficient Block Sampling Strategy for Online Aggregation in the Cloud
• Computing Probability Threshold Set Similarity on Probabilistic Sets
• Region-aware Top-k Similarity Search
• A Partition-Based Bi-directional Filtering Method for String Similarity JOINs
• Fast Multiway Maximum Margin Clustering Based on Genetic Algorithm via the NystrÖm Method
• Short Papers
• DTMF: A User Adaptive Model for Hybrid Recommendation
• An Adaptive Skew Handling Join Algorithm for Large-scale Data Analysis
• NokeaRM: Employing Non-key Attributes in Record Matching
• Efficient Foreign Key Discovery Based on Nearest Neighbor Search
• OntoEvent: An Ontology-Based Event Description Language for Semantic Complex Event Processing
• Differential Trust Propagation with Community Discovery for Link-Based Web Spam Demotion
• Inferring User Preference in Good Abandonment from Eye Movements
• Private Range Queries on Outsourced Databases
• Efficient Influence Maximization Based on Three Degrees of Influence Theory
• Bichromatic Reverse kNN Query Algorithm on Road Network Distance
• IIRS: A Novel Framework of Identifying Commodity Entities on E-commerce Big Data
• Extracting Appraisal Expressions from Short Texts
• Friendship Link Recommendation Based on Content Structure Information
• Overlapping Community Detection in Directed Heterogeneous Social Network
• Efficient MapReduce-Based Method for Massive Entity Matching
• The Role of Physical Location in Our Online Social Networks
• Hierarchical Community Evolution Mining from Dynamic Networks
• Exploiting Conceptual Relations of Sentences for Multi-document Summarization
• Towards Narrative Information Systems
• Maximizing the Spread of Competitive Influence in a Social Network Oriented to Viral Marketing
• SEMR: Secure and Efficient Multi-dimensional Range Query Processing in Two-tiered Wireless Sensor Networks
• A Sampling-Based Framework for Crowdsourced Select Query with Multiple Predicates
• A Customized Schema Design Framework for Multi-tenant Database
• A Multi-attribute Probabilistic Matrix Factorization Model for Personalized Recommendation
• A Novel Knowledge Extraction Framework for Resumes Based on Text Classifier
• SimRank Based Top-k Query Aggregation for Multi-Relational Networks
• On Dynamic Top-k Influence Maximization
• Community Based Spammer Detection in Social Networks
• LDM: A DTD Schema Mapping Language Based on Logic Patterns
• Effective Sampling of Points of Interests on Maps Based on Road Networks
• Associated Index for Big Structured and Unstructured Data
• Demo Papers
• Web Knowledge Base Improved OCR Correction for Chinese Business Cards
• Shortest Path and Word Vector Based Relation Representation and Clustering
• CrowdSR: A Crowd Enabled System for Semantic Recovering of Web Tables
• A Personalized News Recommendation System Based on Tag Dependency Graph
• SmartInt: A Demonstration System for the Interaction Between Schema Mapping and Record Matching
• CDSG: A Community Detection System Based on the Game Theory.

This book constitutes the refereed proceedings of the 16th International Conference on Web-Age Information Management, WAIM 2015, held in Qingdao, China, in June 2015. The 33 full research papers, 31 short research papers, and 6 demonstrations were carefully reviewed and selected from 164 submissions. The focus of the conference is on following topics: advanced database and web applications, big data analytics big data management, caching and replication, cloud computing, content management, crowdsourcing data and information quality, data management for mobile and pervasive computing, data management on new hardware, data mining, data provenance and workflow, data warehousing and OLAP, deep web, digital libraries, entity resolution and entity linking, and graph data management, and RDF.

• Knowledge Extraction: Lexical and Entity
• Knowledge Extraction: Relation
• Knowledge Extraction: Event
• Knowledge Applications: Question Answering, Dialogue, Decision Support, and Recommendation.

This book constitutes the refereed proceedings of the 5th China Conference on Knowledge Graph and Semantic Computing, CCKS 2020, held in Nanchang, China, in November 2020. The 26 revised full papers presented were carefully reviewed and selected from 173 submissions. The papers are organized in topical sections on knowledge extraction: lexical and entity; knowledge extraction: relation; knowledge extraction: event; knowledge applications: question answering, dialogue, decision support, and recommendation.

海归富二代, 青年建筑设计师王小莫(孙艺洲 饰)本想入职后大显身手, 却被公司分配照顾已经离退休的, 患有脑瘤疾病的老劳模时长工(李保田 饰). 面对对待自己横挑鼻子竖挑眼的爷爷辈的老劳模, 王小莫和女友(周秀娜 饰)洋相百出, 历尽"磨难", 但俩 人同时也对时长工的感情经历产生了好奇和"一探究竟"的兴趣. 进而竟发现了年轻时的时长工(马元 饰)与留苏技术员薛亚兰(陈乔恩 饰)在人民大会堂工地上发生的一段旷世绝恋 ... 海归富二代, 青年建筑设计师王小莫(孙艺洲 饰)本想入职后大显身手, 却被公司分配照顾已经离退休的, 患有脑瘤疾病的老劳模时长工(李保田 饰). 面对对待自己横挑鼻子竖挑眼的爷爷辈的老劳模, 王小莫和女友(周秀娜 饰)洋相百出, 历尽"磨难", 但俩 人同时也对时长工的感情经历产生了好奇和"一探究竟"的兴趣. 进而竟发现了年轻时的时长工(马元 饰)与留苏技术员薛亚兰(陈乔恩 饰)在人民大会堂工地上发生的一段旷世绝恋 ...