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- Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks355
A novel framework based on Recurrent Neural Networks (RNN) is introduced that directly models the dependency on user's sequential behaviors into the click prediction process through the recurrent structure in RNN.
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- Knowledge Graph Embedding With Iterative Guidance From Soft Rules247
Experimental results show that with rule knowledge injected iteratively, RUGE achieves significant and consistent improvements over state-of-the-art baselines; and despite their uncertainties, automatically extracted soft rules are highly beneficial to KG embedding, even those with moderate confidence levels.
- Query dependent pseudo-relevance feedback based on wikipedia245
This work proposes and proposes and studies the effectiveness of three methods for expansion term selection, each modeling the Wikipedia based pseudo-relevance information from a different perspective, and incorporates the expansion terms into the original query and uses language modeling IR to evaluate these methods.
- Real-time Multi-Class Helmet Violation Detection Using Few-Shot Data Sampling Technique and YOLOv8216
This study proposes a robust real-time helmet violation detection system that utilizes a unique data processing strategy, referred to as few-shot data sampling, to develop a robust model with fewer annotations, and a single-stage object detection model, YOLOv8 (You Only Look Once Version 8), for detecting helmet violations in real- time from video frames.
- A probabilistic model for retrospective news event detection205
This work proposes a probabilistic model to incorporate both content and time information in a unified framework for retrospective news event detection and builds an interactive RED system, HISCOVERY, which provides additional functions to present events, Photo Story and Chronicle.
- Exploiting parallel texts for word sense disambiguation182
This paper evaluates an approach to automatically acquire sense-tagged training data from English-Chinese parallel corpora, which are then used for disambiguating the nouns in the SENSEVAL-2 English lexical sample task.
- Improving Knowledge Graph Embedding Using Simple Constraints158
The potential of using very simple constraints to improve KG embedding is investigated, examining non-negativity constraints on entity representations and approximate entailment constraints on relation representations to improve model interpretability.
- Question-answer topic model for question retrieval in community question answering127
A novel Question-Answer Topic Model (QATM) is proposed to learn the latent topics aligned across the question-answer pairs to alleviate the lexical gap problem, with the assumption that a question and its paired answer share the same topic distribution.
- Relation Extraction with Multi-instance Multi-label Convolutional Neural Networks.125
This paper proposes a multi-instance multi-label convolutional neural network for distantly supervised RE, which first relaxes the expressed-at-least-once assumption, and employs cross-sentence max-pooling so as to enable information sharing across different sentences.
- A novel refinement approach for text categorization113
The results indicate that in each case, the refined classifiers achieve significant performance improvement over the base classifiers used, and the performance of the Refined Centroid Classifier implemented is comparable, if not better, to that of state-of-the-art support vector machine (SVM)-based classifier, but offers a much lower computational cost.
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- Constructing and Embedding Abstract Event Causality Networks from Text Snippets93
Experimental results demonstrate that the abstract causality network is effective for discovering high-level causality rules behind specific causal events, and the embedding models perform better than state-of-the-art link prediction techniques in predicting events.
- Simulation and control of skeleton-driven soft body characters91
A physics-based framework for simulation and control of human-like skeleton-driven soft body characters that couple the skeleton dynamics and the soft body dynamics to enable two-way interactions between the skeleton, the skin geometry, and the environment.
- Global Dynamic Path Planning Fusion Algorithm Combining Jump-A* Algorithm and Dynamic Window Approach82
The experimental results show that the new fusion algorithm proposed in this paper can not only effectively solve the problem of non-continuous curvature and excessive turning angle at the turning points of the path planned by jump-A* algorithm, but also improve the smoothness of the course and the global optimality.
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- Automatic Classification of Cervical Cells Using Deep Learning Method65
The potential of a deep learning model to automatically distinguish abnormal cells from normal cells is explored in cervical cancer screening data collected from the fourth central hospital of Baoding city, China.
- Learning to rank for question routing in community question answering63
A general framework based on the learning to rank concepts for QR is proposed, which can both outperform the traditional query likelihood language model (QLLM) as well as the state-of-the-art Latent Dirichlet Allocation based model (LDA).
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- Dual role model for question recommendation in community question answering57
This paper is the first to systematically investigate the distinctions between the two roles and their different influences on the performance of question recommendation in CQA, and proposes a Dual Role Model (DRM) to model the dual roles of users effectively.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-14. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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