Zhiyong Feng

Intelligent RDD Management for High Performance In-Memory Computing in Spark

2017

Spark is a pervasively used in-memory computing framework in the era of big data, and can greatly accelerate the computation speed by wrapping the accessed data as resilient distribution datasets (RDDs) and storing these datasets …

FESR: A Framework for Eliciting Security Requirements Based on Integration of Common Criteria and Weakness Detection Formal Model

2017

It is critical and foremost to come up with the corresponding security requirements first which the following implementations are based on. However, previous security requirement elicitation work based on Common Criteria (CC) rarely addresses the …

Automatic Modulation Classification of Overlapped Sources Using Multi-Gene Genetic Programming With Structural Risk Minimization Principle

2018 · IEEE Access

As the spectrum environment becomes increasingly crowded and complicated, primary users may be interfered by secondary users and other illegal users. Automatic modulation classification (AMC) of a single source cannot recognize the overlapped sources. Consequently, …

Siamese-Based BiLSTM Network for Scratch Source Code Similarity Measuring

2020

As a popular block-based programming language, Scratch attracts considerable attention in society and educational fields. Code similarity measuring is a major research direction in Scratch, which plays a significant role in clone detection and project …

Function-words Adaptively Enhanced Attention Networks for Few-Shot Inverse Relation Classification

2022

The relation classification is to identify semantic relations between two entities in a given text. While existing models perform well for classifying inverse relations with large datasets, their performance is significantly reduced for few-shot learning. …

Learning Disentangled Semantic Representations for Zero-Shot Cross-Lingual Transfer in Multilingual Machine Reading Comprehension

2022 · arXiv (Cornell University)

Multilingual pre-trained models are able to zero-shot transfer knowledge from rich-resource to low-resource languages in machine reading comprehension (MRC). However, inherent linguistic discrepancies in different languages could make answer spans predicted by zero-shot transfer violate …

High-level preferences as positive examples in contrastive learning for multi-interest sequential recommendation

2024 · Research Square

Abstract The sequential recommendation task based on the multi-interest framework aims to model multiple interests of users from different aspects to predict their future interactions. However, researchers rarely consider the differences in features between the …

TUT4CRS: Time-aware User-preference Tracking for Conversational Recommendation System

2024

The Conversational Recommendation System (CRS) aims to capture user dynamic preferences and provide item recommendations based on multi-turn conversations. However, effectively modeling these dynamic preferences faces challenges due to conversational limitations, which mainly manifests as …