158 Result(s)
within
Chapter
Yao **xi
Data Mining and Knowledge Discovery
Information Storage and Retrieval
Information Systems Applications (incl. Internet)
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Chapter and Conference Paper
Exploiting Spatial Attention and Contextual Information for Document Image Segmentation
We propose a new framework of combining an attention mechanism with a conditional random field to deal with a document image segmentation task. The framework aims to recognize homogeneous regions, e.g. text, f...
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Chapter and Conference Paper
Bi-granularity Adversarial Training for Non-factoid Answer Retrieval
Answer Retrieval is a task of automatically retrieving relevant answers towards a specific question. The recent studies, in this field, have witnessed the vast success of non-factoid QA methods which leverage ...
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Chapter and Conference Paper
\(\mathbb {PSG}\) : Local Privacy Preserving Synthetic Social Graph Generation
Social graph, as a representation of the network topology, contains users’ social relationship. In order to obtain a social graph, a server requires users to submit their relationships. As we know, using or pu...
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Chapter and Conference Paper
Location Differential Privacy Protection in Task Allocation for Mobile Crowdsensing Over Road Networks
Mobile Crowdsensing (MCS) platforms often require workers to provide their locations for task allocation, which may cause privacy leakage
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Chapter and Conference Paper
Loopster++: Termination Analysis for Multi-path Linear Loop
Loop structure is widely adopted in many applications, e.g. collaborative applications, social network applications, and edge computing. And the termination of the loop is of great significance to the correctness...
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Chapter and Conference Paper
Clustering Study of Crowdsourced Test Report with Multi-source Heterogeneous Information
Crowdsourced testing is an emerging testing method in the field of software testing and industrial practice. Crowdsourced testing can provide a more realistic user experience. But crowdsourced workers are inde...
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Chapter
A Data Services Composition Approach for Continuous Query on Social Media Streams
We witness a rapid increase in the number of social media streams due to development of Web2.0, IoT and Cloud Computing technology. These sources include both traditional relational databases and streaming dat...
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Chapter and Conference Paper
Learning to Fuse Multiple Semantic Aspects from Rich Texts for Stock Price Prediction
Stock price prediction is challenging due to the non-stationary fluctuation of stock price, which can be influenced by the stochastic trading behaviors in the market. In recent years, researchers have focused ...
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Chapter and Conference Paper
Classifying Quality Centrality for Source Localization in Social Networks
Source localization, the process of estimating the originator of an epidemic outbreak or rumor propagation in a network, is an important issue in epidemiology and sociology. With the graph topology of the unde...
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Chapter and Conference Paper
Model and Practice of Crowd-Based Education
Based on connectivism pedagogy crowd-based education provides a practical method to extensively exploit wisdoms of core learners in education organization and external crowds on Internet. However, when applyin...
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Chapter and Conference Paper
Personalized Item-of-Interest Recommendation on Storage Constrained Smartphone Based on Word Embedding Quantization
In recent years, word embedding models receive tremendous research attentions due to their capability of capturing textual semantics. This study investigates the issue of employing word embedding models into r...
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Chapter and Conference Paper
Sub2Vec: Feature Learning for Subgraphs
Network embeddings have become very popular in learning effective feature representations of networks. Motivated by the recent successes of embeddings in natural language processing, researchers have tried to ...
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Chapter and Conference Paper
Processing Missing Information in Big Data Environment
How to handle missing information is essential for system efficiency and robustness in the field of the database. Missing information in big data environment tends to have richer semantics, leading to more com...
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Chapter and Conference Paper
Mining POI Alias from Microblog Conversations
In location-based analysis for microblogs, it is important to know if two toponyms refer to the same point-of-interest, i.e., alias. However, existing online knowledge bases are often incomplete or inaccurate ...
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Chapter and Conference Paper
Data-Augmented Regression with Generative Convolutional Network
Generative adversarial networks (GAN)-based approaches have been extensively investigated whereas GAN-inspired regression (i.e., numeric prediction) has rarely been studied in image and video processing domain...
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Chapter and Conference Paper
Cross-Scenario Inference Based Event-Event Relation Detection
Event-Event Relation Detection (RD \(_{2e}\) ) aims to detect the relations between a pair of news events, su...
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Chapter and Conference Paper
Causal Discovery with Bayesian Networks Inductive Transfer
Bayesian networks (BNs) is a dominate model for representing causal knowledge with uncertainty. Causal discovery with BNs requiring large amount of training data for learning BNs structure. When confronted wit...
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Chapter and Conference Paper
\(R^2\) -Tree: An Efficient Indexing Scheme for Server-Centric Data Center Networks
Index plays a very important role in cloud storage systems, which can support efficient querying tasks for data-intensive applications. However, most of existing indexing schemes for data centers focus on one ...
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Chapter and Conference Paper
Community Structure Based Shortest Path Finding for Social Networks
With the rapid expansion of communication data, research about analyzing social networks has become a hotspot. Finding the shortest path (SP) in social networks can help us to investigate the potential social ...
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Chapter and Conference Paper
Cost-Sensitive Reference Pair Encoding for Multi-Label Learning
Label space expansion for multi-label classification (MLC) is a methodology that encodes the original label vectors to higher dimensional codes before training and decodes the predicted codes back to the label...
