260 Result(s)
within
Computer Science
Data Mining and Knowledge Discovery
Database Management
**u Tao
Chapter
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Chapter and Conference Paper
A Phrase-Level Attention Enhanced CRF for Keyphrase Extraction
Since sequence labeling-based methods take into account the dependencies between neighbouring labels, they have been widely used for keyphrase prediction. Existing methods mainly focus on the word-level sequen...
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Chapter and Conference Paper
A Robust Reversible Data Hiding Algorithm Based on Polar Harmonic Fourier Moments
The Robust Reversible Data Hiding (RRDH) algorithm can recover both the secret data and the cover image entirely from an intact stego image, and can still restore the secret message comprehensively even if the...
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Chapter and Conference Paper
NegT5: A Cross-Task Text-to-Text Framework for Negation in Question Answering
Negation is a fundamental grammatical construct that plays a crucial role in understanding QA tasks. It has been revealed that models trained with SQuAD1 still produce original responses when presented with ne...
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Chapter and Conference Paper
RL-Based CEP Operator Placement Method on Edge Networks Using Response Time Feedback
The placement of operators in Complex Event Processing (CEP) services, handling real-time data with DAGs, faces challenges due to the NP-hard nature and edge environment complexity. Prior research by Cai et al...
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Chapter and Conference Paper
Optimally Blending Honeypots into Production Networks: Hardness and Algorithms
Honeypot is an important cyber defense technique that can expose attackers’ new attacks (e.g., zero-day exploits). However, the effectiveness of honeypots has not been systematically investigated, beyond the r...
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Chapter and Conference Paper
Redactable Blockchain in the Permissioned Setting
As a momentous attribute of blockchains, the immutability ensures the integrity and credibility of historical data, but it is inevitably abused to spread illegal content and does not meet certain requirements ...
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Chapter and Conference Paper
TPFL: Test Input Prioritization for Deep Neural Networks Based on Fault Localization
DNN testing is a critical way to guarantee the quality of DNNs. To obtain test oracle information, DNN testing requires a huge cost to label test inputs, which greatly affects the efficiency of DNN testing. To...
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Chapter and Conference Paper
Tackling Non-stationarity in Decentralized Multi-Agent Reinforcement Learning with Prudent Q-Learning
Multi-Agent Reinforcement Learning (MARL) is challenging due to the non-stationary issue of an agent’s learning environment caused by multiple co-evolving agents, i.e., the uncertainty rises with multiple agen...
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Chapter and Conference Paper
Sensor Data Normalization Among Heterogeneous Smartphones for Implicit Authentication
Nowadays, smartphones have become an important part in people’s life. Existing traditional explicit authentication mechanisms can hardly protect the privacy of users, which makes implicit authentication mechan...
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Chapter and Conference Paper
Evaluating the Parallel Execution Schemes of Smart Contract Transactions in Different Blockchains: An Empirical Study
In order to increase throughput, more and more blockchains begin to provide the ability to execute smart contract transactions in parallel. However, there is currently no research work on evaluating parallel e...
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Chapter and Conference Paper
Market-Aware Dynamic Person-Job Fit with Hierarchical Reinforcement Learning
Person-Job Fit (PJF) is the core of online recruitment. Several recent methods took PJF as a preference-learning problem, and tried to learn two-sided preferences from their historical behaviors. However, they...
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Chapter and Conference Paper
A Joint Framework for Explainable Recommendation with Knowledge Reasoning and Graph Representation
With the development of recommendation systems (RSs), researchers are no longer only satisfied with the recommendation results, but also put forward requirements for the recommendation reasons, which helps imp...
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Chapter and Conference Paper
Fast Fourier Orthogonalization over NTRU Lattices
FALCON is an efficient and compact lattice-based signature scheme. It is also one of the round 3 finalists in the NIST PQC standardization process. The core of FALCON is a trapdoor sampling algorithm, which ha...
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Chapter and Conference Paper
A Deep Learning Framework for Removing Bias from Single-Photon Emission Computerized Tomography
After being photographed by medical equipment, noise in the unprocessed medical image is removed through manual processing and correction to create a proper medical image. However, manually processing medical ...
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Chapter and Conference Paper
Out-of-Domain Semantics to the Rescue! Zero-Shot Hybrid Retrieval Models
The pre-trained language model (eg, BERT) based deep retrieval models achieved superior performance over lexical retrieval models (eg, BM25) in many passage retrieval tasks. However, limited work has been done to...
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Chapter and Conference Paper
Coreference Resolution with Syntax and Semantics
Recent years have witnessed a widespread increase of interest in coreference resolution (CR) in the natural language processing (NLP) community. While most research efforts have focused on the span-based metho...
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Chapter and Conference Paper
Gated Hypergraph Neural Network for Scene-Aware Recommendation
To improve e-commercial recommender systems, researchers have never stopped exploring the interactions between users and items. Unfortunately, most existing methods only explore one or some certain components ...
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Chapter and Conference Paper
Tipster: A Topic-Guided Language Model for Topic-Aware Text Segmentation
The accurate segmentation and structural topics of plain documents not only meet people’s reading habit, but also facilitate various downstream tasks. Recently, some works have consistently given positive hint...
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Chapter and Conference Paper
Diversify Search Results Through Graph Attentive Document Interaction
The goal of search result diversification is to retrieve diverse documents to meet as many different information needs as possible. Graph neural networks provide a feasible way to capture the sophisticated rel...
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Chapter and Conference Paper
Leveraging Search History for Improving Person-Job Fit
As the core technique of online recruitment platforms, person-job fit can improve hiring efficiency by accurately matching job positions with qualified candidates. However, existing studies mainly focus on the re...
