22 Result(s)
within
Jungang Xu
Computer Science
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Article
Correction to: HierMDS: a hierarchical multi-document summarization model with global–local document dependencies
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Article
TransETA: transformer networks for estimated time of arrival with local congestion representation
Estimated time of arrival (ETA) is an estimate of the vehicle travel time from the origin to destination in the roadworks. From the perspective of travel planning or resource allocation, accurate ETA is signif...
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Article
HierMDS: a hierarchical multi-document summarization model with global–local document dependencies
Multi-document summarization (MDS) has attracted increasing attention in recent years. Most existing MDS systems simply encode the flat connected sequence of multiple documents, which limits the representation...
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Chapter and Conference Paper
KAAS: A Keyword-Aware Attention Abstractive Summarization Model for Scientific Articles
In this work, we focus on abstractive summarization methods for assisting medical researchers in effectively managing information. Particularly, we introduce a COVID-19-related summarization dataset (COVID-SUM...
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Article
A two-step abstractive summarization model with asynchronous and enriched-information decoding
Most sequence-to-sequence abstractive summarization models generate the summaries based on the source article and the generated words, but they often neglect the future information implied in the un-generated ...
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Chapter and Conference Paper
LBNet: A Model for Judicial Reading Comprehension
In this paper, a new model for judicial reading comprehension called LBNet that combines an end-to-end network with a BERT structure is proposed, which aims to answer questions from a given passage in judicial...
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Chapter and Conference Paper
K2RDF: A Distributed RDF Data Management System on Kudu and Impala
The Resource Description Framework (RDF) has been widely used in various applications or services as a model for displaying, sharing and connecting data. With the increase of RDF data scale, distributed RDF da...
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Chapter and Conference Paper
GCM-Bench: A Benchmark for RDF Data Management System on Microorganism Data
The biological data is growing up to an unprecedented scale, such as microorganism knowledge graph organized by biologists, which is represented by Resource Description Framework (RDF) data model. In this pape...
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Chapter and Conference Paper
A Novel Image Captioning Method Based on Generative Adversarial Networks
Although the image captioning methods based on RNN has made great progress in recent years, these are often lacking in variability and ignore some minor information. In this paper, a novel image captioning me...
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Chapter and Conference Paper
A Recurrent Neural Network Language Model Based on Word Embedding
Language model is one of the basic research issues of natural language processing, and which is the premise for realizing more complicated tasks such as speech recognition, machine translation and question ans...
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Chapter and Conference Paper
A Study on Performance Sensitivity to Data Sparsity for Automated Essay Scoring
Automated essay scoring (AES) attempts to rate essays automatically using machine learning and natural language processing techniques, ho** to dramatically reduce the manual efforts involved. Given a target ...
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Article
Open AccessA Feedback-Based Approach to Utilizing Embeddings for Clinical Decision Support
Clinical Decision Support (CDS) is widely seen as an information retrieval (IR) application in the medical domain. The goal of CDS is to help physicians find useful information from a collection of medical ar...
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Chapter and Conference Paper
An Improved Convolutional Neural Network for Sentence Classification Based on Term Frequency and Segmentation
Recently, Sentence classification is a ubiquitous Natural Language Processing (NLP) task and deep learning is proved to be a kind of methods that has a significant effect in this area. In this work, we propose...
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Chapter and Conference Paper
A Study of Distributed Semantic Representations for Automated Essay Scoring
Automated essay scoring (AES) applies machine learning and NLP techniques to automatically rate essays written in an educational setting, by which the workload of human raters is considerably reduced. Current ...
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Chapter and Conference Paper
Integrating Feedback-Based Semantic Evidence to Enhance Retrieval Effectiveness for Clinical Decision Support
The goal of Clinical Decision Support (CDS) is to help physicians find useful information from a collection of medical articles with respect to the given patient records, in order to take the best care of thei...
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Chapter and Conference Paper
A Document Modeling Method Based on Deep Generative Model and Spectral Hashing
One of the most critical challenges in document modeling is the efficiency of the extraction of the high level representations. In this paper, a document modeling method based on deep generative model and spec...
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Chapter and Conference Paper
A Set-Based Training Query Classification Approach for Twitter Search
Learning to rank is a popular technique of building a ranking model for Twitter search by utilizing a rich list of features. As most learning to rank algorithms are supervised, their effectiveness is heavily a...
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Chapter and Conference Paper
Multilevel Syntactic Parsing Based on Recursive Restricted Boltzmann Machines and Learning to Rank
Syntactic parsing is one of the central tasks in Natural Language Processing. In this paper, a multilevel syntactic parsing algorithm is proposed, which is a three-level model with innovative combinations of e...
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Chapter and Conference Paper
Robust Corner Detection Based on Bilateral Filter in Direct Curvature Scale Space
In traditional Curvature Scale Space (CSS) corner detection algorithms, Gaussian filter is used to remove noise existing in canny edge detection results. Unfortunately, Gaussian filter will reduce the precisio...
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Chapter and Conference Paper
A Document Clustering Algorithm Based on Semi-constrained Hierarchical Latent Dirichlet Allocation
The bag-of-words model used for some clustering methods is often unsatisfactory as it ignores the relationship between the important terms that do not cooccur literally. In this paper, a document clustering al...
