Search Results for author:
Found 26 papers, 4 papers with code
IR&TM-NJUST@CLSciSumm 20
Unlike the methods used in CL-SciSumm 2019, we construct inputs of models based on word vectors and add deep learning models for classification this year.
UI Layout Generation with LLMs Guided by UI Grammar
The recent advances in Large Language Models (LLMs) have stimulated interest among researchers and industry professionals, particularly in their application to tasks concerning mobile user interfaces (UIs).
Automatic Recognition and Classification of Future Work Sentences from Academic Articles in a Specific Domain
This paper presents methods to automatically extract FWS from academic papers and classify them according to the different future directions embodied in the paper's content.
Exploring the Distribution Regularities of User Attention and Sentiment toward Product Aspects in Online Reviews
[Purpose] To better understand the online reviews and help potential consumers, businessmen, and product manufacturers effectively obtain users' evaluation on product aspects, this paper explores the distribution regularities of user attention and sentiment toward product aspects from the temporal perspective of online reviews.
A Review on Method Entities in the Academic Literature: Extraction, Evaluation, and Application
With the advancement of sciences, many scientific methods are being proposed, modified, and used in academic literature.
Does Attention Mechanism Possess the Feature of Human Reading? A Perspective of Sentiment Classification Task
Then, the machine attention values of each sentence were learned from a sentiment classification model.
Which structure of academic articles do referees pay more attention to?: perspective of peer review and full-text of academic articles
Purpose The purpose of this paper is to explore which structures of academic articles referees would pay more attention to, what specific content referees focus on, and whether the distribution of PRC is related to the citations.
Using Hashtags to Analyze Purpose and Technology Application of Open-Source Project Related to COVID-19
The study results show an imbalance in the number of projects with varying functionalities in the GitHub community, i. e., applications account for more than half of the projects.
Cross-domain Federated Object Detection
Federated learning can enable multi-party collaborative learning without leaking client data.
Enhancing Identification of Structure Function of Academic Articles Using Contextual Information
In the research on identifying the structure function of chapters in academic articles, only a few studies used the deep learning model and explored the optimization for feature input.
Enhancing Keyphrase Extraction from Academic Articles with their Reference Information
This indicates the usefulness of reference information on keyphrase extraction of academic papers and provides a new idea for the following research on automatic keyphrase extraction.
Impacts Towards a comprehensive assessment of the book impact by integrating multiple evaluation sources
Meanwhile, relying on a single resource for book assessment may lead to the risk that the evaluation results cannot be obtained due to the lack of the evaluation data, especially for newly published books.
Breaking Community Boundary: Comparing Academic and Social Communication Preferences regarding Global Pandemics
The research results from 50, 338 articles and 927, 266 corresponding tweets mentioning the articles revealed communication differences about global pandemics between the academic and the social communities regarding the consistency of research recognition and the preferences for particular research topics.
Using Full-text Content of Academic Articles to Build a Methodology Taxonomy of Information Science in China
Accordingly, the research methodology entities were clustered and the basic methodology taxonomy was expanded using the clustering results to obtain a methodology taxonomy with more levels.
Characterizing References from Different Disciplines: A Perspective of Citation Content Analysis
Analyzing the distribution characteristics of references from different disciplines in research articles is basic to detecting the sources of referred information and identifying contributions of different disciplines.
Chronological Citation Recommendation with Time Preference
Citation recommendation is an important task to assist scholars in finding candidate literature to cite.
Using the Full-text Content of Academic Articles to Identify and Evaluate Algorithm Entities in the Domain of Natural Language Processing
To this end, this article takes the field of natural language processing (NLP) as an example and identifies algorithms from academic papers in the field.
Enhancing Keyphrase Extraction from Microblogs using Human Reading Time
Moreover, we propose strategies to make eye fixation duration more effective on keyphrase extraction.
Spatio-Temporal Hybrid Graph Convolutional Network for Traffic Forecasting in Telecommunication Networks
We conduct extensive experiments on real-world traffic datasets collected from telecommunication networks.
Analyzing Linguistic Complexity and Scientific Impact
In this context, scientific writing increasingly plays an important role in scholars' scientific careers.
Using Human Attention to Extract Keyphrase from Microblog Post
Thus, this paper aims to integrate human attention into keyphrase extraction models.
Examining Scientific Writing Styles from the Perspective of Linguistic Complexity
The observations suggest marginal differences between groups in syntactical and lexical complexity.
Encoding Conversation Context for Neural Keyphrase Extraction from Microblog Posts
Existing keyphrase extraction methods suffer from data sparsity problem when they are conducted on short and informal texts, especially microblog messages.
Online shopping behavior study based on multi-granularity opinion mining: China vs. America
Second, international customer behavior study is made easier by integrating tools for multilingual opinion mining.
Measuring Book Impact Based on the Multi-granularity Online Review Mining
In this study, we measure the impacts of academic books by multi-granularity mining online reviews, and we identify factors that affect a book's impact.
