Jing Li

Tendency of Restaurant Reviews Mining Model Combining FP-Tree Algorithm

2015

A restaurant review tendentious mining method that combines FP-Tree algorithm is presented to dig and identify high-frequency noun pairs in reviews associated with services, the environment, food, to name just a few, by mining association …

Research on the Strategic Development of the Reform and Transformation of Independent College to Application-Oriented College-Deepen the reform of the system and mechanism of application-oriented college

2016

Independent colleges as local colleges, after more than 10 years of development, from initial infrastructure development to the current internal development, based on Parent College rapid promotion, has playing a great role in the whole …

Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs

2016 · arXiv (Cornell University)

Using unitary (instead of general) matrices in artificial neural networks (ANNs) is a promising way to solve the gradient explosion/vanishing problem, as well as to enable ANNs to learn long-term correlations in the data. This …

Leveraging Official Content and Social Context to Recommend Software Documentation

2018 · IEEE Transactions on Services Computing

For an unfamiliar Application Programming Interface (API), software developers often access the official documentation to learn its usage, and post questions related to this API on social question and answering (Q&A) sites to seek solutions. …

Achieving Efficient and Secure Data Acquisition for Cloud-supported Internet of Things in Smart Grid

2018 · arXiv (Cornell University)

Cloud-supported Internet of Things (Cloud-IoT) has been broadly deployed in smart grid systems. The IoT front-ends are responsible for data acquisition and status supervision, while the substantial amount of data is stored and managed in …

Two-stage iterative Procrustes match algorithm and its application for VQ-based speaker verification

2018 · arXiv (Cornell University)

In the past decades, Vector Quantization (VQ) model has been very popular across different pattern recognition areas, especially for feature-based tasks. However, the classification or regression performance of VQ-based systems always confronts the feature mismatch …

Continuous-Time Analysis of the Bitcoin and Prism Backbone Protocols

2020 · arXiv (Cornell University)

Bitcoin is a peer-to-peer payment system proposed by Nakamoto in 2008. Based on the Nakamoto consensus, Bagaria, Kannan, Tse, Fanti, and Viswanath proposed the Prism protocol in 2018 and showed that it achieves near-optimal blockchain …

Query Suggestions as Summarization in Exploratory Search

2021

Query suggestions have been shown to benefit users performing information retrieval tasks. In exploratory search, however, users may lack the necessary domain knowledge to assess the relevance of query suggestions with respect to their information …

Taming Overconfident Prediction on Unlabeled Data from Hindsight

2021 · arXiv (Cornell University)

Minimizing prediction uncertainty on unlabeled data is a key factor to achieve good performance in semi-supervised learning (SSL). The prediction uncertainty is typically expressed as the \emph{entropy} computed by the transformed probabilities in output space. …

Quantum K-nearest neighbor classification algorithm based on Hamming distance

2021 · arXiv (Cornell University)

K-nearest neighbor classification algorithm is one of the most basic algorithms in machine learning, which determines the sample's category by the similarity between samples. In this paper, we propose a quantum K-nearest neighbor classification algorithm …

Public opinion early warning technology of power supply service based on topic web crawler

2022 · 5th International Conference on Computer Information Science and Application Technology (CISAT 2022)

To improve the response time of public opinion on early warning of power service and expand the coverage of early warning, this time, combined with the theme of web crawler technology, the research on public …

BIFLC: A Blockchain and IPFS-Based Multi-Consensus Federated Learning Framework

2023

Federated learning is an efficient technology that implements distributed model training among multiple data sources with local data, and can realize data privacy protection and data sharing computing .However, existing federated learning models may involve …

A Survey on Deep Learning for Named Entity Recognition : Extended Abstract

2023

Named entity recognition (NER) is the task to identify text spans that mention named entities, and to classify them into predefined categories such as person, location, organization, etc. In recent years, deep learning, empowered by …

OR-AutoRec: An Outlier-Resilient Autoencoder-based Recommendation model

2022

Deep neural network (DNN) is widely adopted to develop the recommender systems (RSs) in recent years due to its powerful non-linear representation learning ability. So far, various sophisticated DNN-based RSs have been achieved to provide …

A Method for Extracting Photovoltaic Panels from High-Resolution Optical Remote Sensing Images Guided by Prior Knowledge

2023 · Remote Sensing

The extraction of photovoltaic (PV) panels from remote sensing images is of great significance for estimating the power generation of solar photovoltaic systems and informing government decisions. The implementation of existing methods often struggles with …

Label Learning Method Based on Tensor Projection

2024 · arXiv (Cornell University)

Multi-view clustering method based on anchor graph has been widely concerned due to its high efficiency and effectiveness. In order to avoid post-processing, most of the existing anchor graph-based methods learn bipartite graphs with connected …

CoSafe: Evaluating Large Language Model Safety in Multi-Turn Dialogue Coreference

2024 · arXiv (Cornell University)

As large language models (LLMs) constantly evolve, ensuring their safety remains a critical research problem. Previous red-teaming approaches for LLM safety have primarily focused on single prompt attacks or goal hijacking. To the best of …

MMMT-IF: A Challenging Multimodal Multi-Turn Instruction Following Benchmark

2024 · ArXiv.org

Evaluating instruction following capabilities for multimodal, multi-turn dialogue is challenging. With potentially multiple instructions in the input model context, the task is time-consuming for human raters and we show LLM based judges are biased towards …

Area under the ROC Curve has the most consistent evaluation for binary classification

2024 · PLoS ONE

The proper use of model evaluation metrics is important for model evaluation and model selection in binary classification tasks. This study investigates how consistent different metrics are at evaluating models across data of different prevalence …

Research on Computer Image Recognition Technology Based on Artificial Intelligence

2024

In order to solve the problem of fast processing for ultra-high-resolution images in embedded systems, this paper proposes a multi-mode tracking and recognition method based on embedded processing architecture, through the construction of a multi-GPU …

Discerning MOS of Video Conferencing via Deep Packet Inspection and Video Context Clues

2025

Monitoring the Mean Opinion Score (MOS) of video conferencing is critical for Internet Service Providers (ISPs) to ensure user satisfaction. However, a significant technical challenge arises: MOS is a subjective measure, while ISPs primarily rely …

SK2Decompile: LLM-based Two-Phase Binary Decompilation from Skeleton to Skin

2025 · arXiv (Cornell University)

Large Language Models (LLMs) have emerged as a promising approach for binary decompilation. However, the existing LLM-based decompilers still are somewhat limited in effectively presenting a program's source-level structure with its original identifiers. To mitigate …

QSEA: Quantum Self-supervised Learning with Entanglement Augmentation

2025 · arXiv (Cornell University)

As an unsupervised feature representation paradigm, Self-Supervised Learning (SSL) uses the intrinsic structure of data to extract meaningful features without relying on manual annotation. Despite the success of SSL, there are still problems, such as …

Audio Adversarial Example Detection Scheme via Re-Attack

2026 · Electronics

Adversarial examples, created by adding small distortions to audio, can fool neural network models and cause automatic speech recognition (ASR) systems to produce incorrect outputs. Most current detection methods rely on the recognition capabilities of …

Noise Label Detection and Correction via Bayesian Weighted Consensus Inference

2026 · Computers

Affected by inter-annotator cognitive differences, fatigue effects, and data poisoning, training data inevitably contains a certain proportion of noise, which severely impairs model performance. Traditional manual verification is costly and inefficient, while existing automatic detection …

Directional Skip-Gram: Explicitly Distinguishing Left and Right Context for Word Embeddings

2018

Yan Song, Shuming Shi, Jing Li, Haisong Zhang. Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers). 2018.

SegBot: A Generic Neural Text Segmentation Model with Pointer Network

2018

Text segmentation is a fundamental task in natural language processing that comes in two levels of granularity: (i) segmenting a document into a sequence of topical segments (topic segmentation), and (ii) segmenting a sentence into …

A trust-based collaborative filtering algorithm for E-commerce recommendation system

2018 · Journal of Ambient Intelligence and Humanized Computing

The rise of e-commerce has not only given consumers more choice but has also caused information overload. In order to quickly find favorite items from vast resources, users are eager for technology by which websites …

DAML: Dual Attention Mutual Learning between Ratings and Reviews for Item Recommendation

2019

Despite the great success of many matrix factorization based collaborative filtering approaches, there is still much space for improvement in recommender system field. One main obstacle is the cold-start and data sparseness problem, requiring better …

RepeatNet: A Repeat Aware Neural Recommendation Machine for Session-Based Recommendation

2019 · Proceedings of the AAAI Conference on Artificial Intelligence

Recurrent neural networks for session-based recommendation have attracted a lot of attention recently because of their promising performance. repeat consumption is a common phenomenon in many recommendation scenarios (e.g., e-commerce, music, and TV program recommendations), …

Neural Attentive Session-based Recommendation

2017

Given e-commerce scenarios that user profiles are invisible, session-based recommendation is proposed to generate recommendation results from short sessions. Previous work only considers the user's sequential behavior in the current session, whereas the user's main …

A Survey on Deep Learning for Named Entity Recognition

2020 · IEEE Transactions on Knowledge and Data Engineering

Named entity recognition (NER) is the task to identify mentions of rigid designators from text belonging to predefined semantic types such as person, location, organization etc. NER always serves as the foundation for many natural …