Journal of Information Science最新文献_第5页

A polyphony of characteristics: An analysis of the categorisation of music’s subgenres 特征复调:音乐子类型分类分析

4区管理学

Journal of Information Science Pub Date : 2023-10-24 DOI: 10.1177/01655515231203511

Philip Hider, Deborah Lee

引用次数: 0

A deep CNN architecture with novel pooling layer applied to two Sudanese Arabic sentiment data sets 将具有新颖池化层的深度CNN架构应用于两个苏丹阿拉伯情感数据集

4区管理学

Journal of Information Science Pub Date : 2023-10-21 DOI: 10.1177/01655515231188341

Mustafa Mhamed, Richard Sutcliffe, Husam Quteineh, Xia Sun, Eiad Almekhlafi, Ephrem Afele Retta, Jun Feng

{"title":"A deep CNN architecture with novel pooling layer applied to two Sudanese Arabic sentiment data sets","authors":"Mustafa Mhamed, Richard Sutcliffe, Husam Quteineh, Xia Sun, Eiad Almekhlafi, Ephrem Afele Retta, Jun Feng","doi":"10.1177/01655515231188341","DOIUrl":"https://doi.org/10.1177/01655515231188341","url":null,"abstract":"Arabic sentiment analysis has become an important research field in recent years. Initially, work focused on Modern Standard Arabic (MSA), which is the most widely used form. Since then, work has been carried out on several different dialects, including Egyptian, Levantine and Moroccan. Moreover, a number of data sets have been created to support such work. However, up until now, no work has been carried out on Sudanese Arabic, a dialect which has 32 million speakers. In this article, two new public data sets are introduced, the two-class Sudanese Sentiment Data set (SudSenti2) and the three-class Sudanese Sentiment Data set (SudSenti3). In the preparation phase, we establish a Sudanese stopword list. Furthermore, a convolutional neural network (CNN) architecture, Sentiment Convolutional MMA (SCM), is proposed, comprising five CNN layers together with a novel Mean Max Average (MMA) pooling layer, to extract the best features. This SCM model is applied to SudSenti2 and SudSenti3 and shown to be superior to the baseline models, with accuracies of 92.25% and 85.23% (Experiments 1 and 2). The performance of MMA is compared with Max, Avg and Min and shown to be better on SudSenti2, the Saudi Sentiment Data set and the MSA Hotel Arabic Review Data set by 1.00%, 0.83% and 0.74%, respectively (Experiment 3). Next, we conduct an ablation study to determine the contribution to performance of text normalisation and the Sudanese stopword list (Experiment 4). For normalisation, this makes a difference of 0.43% on two-class and 0.45% on three-class. For the custom stoplist, the differences are 0.82% and 0.72%, respectively. Finally, the model is compared with other deep learning classifiers, including transformer-based language models for Arabic, and shown to be comparable for SudSenti2 (Experiment 5).","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":"14 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135513261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A social diagnosis mechanism for healthcare knowledge sharing 医疗保健知识共享的社会诊断机制

4区管理学

Journal of Information Science Pub Date : 2023-10-19 DOI: 10.1177/01655515231199929

Lien-Fa Lin, Yung-Ming Li, Yen-Chen Lin

引用次数: 0

A fieldwork manual as a regulatory device: Instructing, prescribing and describing documentation work 作为监管工具的野外工作手册:指导、规定和描述文件工作

4区管理学

Journal of Information Science Pub Date : 2023-10-19 DOI: 10.1177/01655515231203506

Isto Huvila, Olle Sköld

引用次数: 0

MNN4Rec: A relation-aware approach based on multi-view news network for news recommendation MNN4Rec:基于多视图新闻网络的关系感知新闻推荐方法

4区管理学

Journal of Information Science Pub Date : 2023-10-18 DOI: 10.1177/01655515231182072

Hao Jiang, Chuanzhen Li, Juanjuan Cai, Jingling Wang

{"title":"MNN4Rec: A relation-aware approach based on multi-view news network for news recommendation","authors":"Hao Jiang, Chuanzhen Li, Juanjuan Cai, Jingling Wang","doi":"10.1177/01655515231182072","DOIUrl":"https://doi.org/10.1177/01655515231182072","url":null,"abstract":"Personalised news recommendation comprises two crucial components: news understanding and user modelling. Previous studies have attempted to model news understanding and user interests using various internal news information and external knowledge graphs (KG). However, they have overlooked the collaborative function of the external KG and the internal information among diverse news and user behaviours, resulting in serious news cold-start problems and poor interpretability of user interests. To address these issues, this article proposes a novel approach called Relation-Aware Approach based on Multi-view News Network for News Recommendation (MNN4Rec). Specifically, MNN4Rec first constructs a Multi-view News Network (MNN), which includes candidate news and user-clicked news, and represents their exclusive multi-view information as heterogeneous nodes. Furthermore, we develop explicit and implicit news relationships and design a special sampling algorithm to search for news co-neighbours. We then use a novel dual-channel graph attention mechanism to obtain the fine-grained news understanding representation. Moreover, we construct explainable user interests by modelling the interaction of user-clicked news through the multi-headed self-attention mechanism in both semantic and relation levels. Finally, we match candidate news understanding with user interests to generate a prediction score for recommendation. Experimental results on Microsoft’s news data set MIND demonstrate that MNN4Rec outperforms existing news-recommendation methods while also mitigating the cold-start problem and enhancing the interpretability of user interests. Our code is available at https://github.com/JiangHaoPG11/MNN4Rec_code .","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135884147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CHV.br: Exploratory study for the development of a consumer health vocabulary (CHV) supported by a network model for Brazilian Portuguese language CHV。基于网络模型的巴西葡萄牙语消费者健康词汇开发的探索性研究

4区管理学

Journal of Information Science Pub Date : 2023-09-30 DOI: 10.1177/01655515231196391

Josceli M Tenorio, Fabrício Landi de Moraes, Ivan Torres Pisa

{"title":"CHV.br: Exploratory study for the development of a consumer health vocabulary (CHV) supported by a network model for Brazilian Portuguese language","authors":"Josceli M Tenorio, Fabrício Landi de Moraes, Ivan Torres Pisa","doi":"10.1177/01655515231196391","DOIUrl":"https://doi.org/10.1177/01655515231196391","url":null,"abstract":"Successful consumer health vocabulary (CHV) models have been engineered and updated by using automatic term extraction techniques from online content. However, the relationship between terms has yet to be mapped. This study aims to describe a CHV model for the Brazilian Portuguese language that is supported by a complex network. The method was split up into three distinct stages: (1) collect and automatically extract terms from structured data sources on the web, such as Unified Medical Language System (UMLS) vocabularies and DBpedia; (2) construct a complex network; and (3) select the terms supported by clustering techniques. A model called CHV.br was developed and supported by a complex network structure which makes connections between the controlled vocabulary and consumer vocabulary and maps semantic relationships as categories, synonyms and related terms. CHV.br contains 146,956 terms, of which 31,439 are UMLS preferred terms and 83,279 are synonyms. The CHV.br is available and powered by Simple Knowledge Organization System and Resource Description Framework standards. The method used in this study showed to be valid for the selection of the candidate terms by connecting the terms from different reliable resources, in addition to expanding the number of terms and their semantic relationships. The content and structure of CHV.br could play a vital role in enhancing the development of consumer-oriented health applications.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136336485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automatic author name disambiguation by differentiable feature selection 基于可微分特征选择的作者姓名自动消歧

4区管理学

Journal of Information Science Pub Date : 2023-09-19 DOI: 10.1177/01655515231193859

ZhiJian Fang, Yue Zhuo, Jinying Xu, Zhechong Tang, Zijie Jia, HuaXiong Zhang

{"title":"Automatic author name disambiguation by differentiable feature selection","authors":"ZhiJian Fang, Yue Zhuo, Jinying Xu, Zhechong Tang, Zijie Jia, HuaXiong Zhang","doi":"10.1177/01655515231193859","DOIUrl":"https://doi.org/10.1177/01655515231193859","url":null,"abstract":"Author name disambiguation (AND) is the task of resolving the ambiguity problem in bibliographic databases, where distinct real-world authors may share the same name or same author may have distinct names. The aim of AND is to split the name-ambiguous entities (articles) into the corresponding authors. Existing AND algorithms mainly focus on designing different similarity metrics between two ambiguous articles. However, most previous methods empirically select and process the features of entities, then use features to predict the similarity by data-driven models. In this article, we are motivated by natural questions: Which features are most useful for splitting name-ambiguous entities? Can they be automatically determined by an optimisation approach rather than heuristic feature engineering? Therefore, we proposed a novel end-to-end differentiable feature selection algorithm, automatically searching the optimal features for AND task (AAND). AAND optimises the discrete feature selection by differentiable Gumbel-Softmax, leading to the joint learning of feature selection policy and similarity prediction model. The experiments are conducted on a benchmark data set, S2AND, which harmonises eight different AND data sets. The results show that the performance of our proposal is superior to the advanced AND methods and feature selection algorithms. Meanwhile, deep insights into AND features are also given.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135107090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Discovering research data management trends from job advertisements using a text-mining approach 使用文本挖掘方法从招聘广告中发现研究数据管理趋势

4区管理学

Journal of Information Science Pub Date : 2023-09-15 DOI: 10.1177/01655515231193845

Naseema Sheriff, R Sevukan

{"title":"Discovering research data management trends from job advertisements using a text-mining approach","authors":"Naseema Sheriff, R Sevukan","doi":"10.1177/01655515231193845","DOIUrl":"https://doi.org/10.1177/01655515231193845","url":null,"abstract":"In today’s data-driven culture, research data management (RDM) is essential for the research community. The demand for reusing research datasets is a challenging and diverse process for the scientific community. Despite this, it is essential in RDM to discover trends and themes using text mining, which is scarce. The purpose of this study is to employ text mining to discover insights from job advertisements associated with RDM profiles, which collected 810 advertisements. We found RDM-related patterns using latent Dirichlet allocation (LDA) and identified three key contexts. The first is ‘research services in libraries’, with the topics of research services, research information, research universities, collection processes and library services. The second context is ‘research data’, which includes RDM, business data, university data, research data, health research, science research, social science research, data centres, data services, statistical software, digital scholarship and digital preservation. The third context is ‘workplace environment’, and the topics are leadership, work development and scientific position. Job title normalisation reveals names such as ‘data librarian’, ‘librarian’, ‘director’, ‘data curator’, ‘data manager’, ‘research data librarian’, ‘data specialist’ and ‘data officer’ are frequently employed. Focusing on titles with a single or double occurrence is new and interesting for developing nations. Reputable institutions such as Harvard, Stanford and the Massachusetts Institute of Technology, as well as countries such as the United States, the United Kingdom, Canada and Germany, are the major participants in RDM practises and services. This discovery will assist higher education institutions, RDM stakeholders, which aid in the formulation of curriculum, and job seekers to familiarise themselves with the themes.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135396503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A model of planned and unplanned information-seeking behaviour 计划和非计划的信息寻求行为模型

4区管理学

Journal of Information Science Pub Date : 2023-09-11 DOI: 10.1177/01655515231196390

Hadi Harati, Alireza Isfandyari-Moghaddam

引用次数: 0

Information architecture on the websites of major American political parties: Qualitative-heuristic assessment and comparative analysis 美国主要政党网站的信息架构:定性启发式评估与比较分析

4区管理学

Journal of Information Science Pub Date : 2023-09-11 DOI: 10.1177/01655515231196392

Paulina Sajna-Kosobucka, Radoslaw Sajna-Kunowsky

{"title":"Information architecture on the websites of major American political parties: Qualitative-heuristic assessment and comparative analysis","authors":"Paulina Sajna-Kosobucka, Radoslaw Sajna-Kunowsky","doi":"10.1177/01655515231196392","DOIUrl":"https://doi.org/10.1177/01655515231196392","url":null,"abstract":"The Internet has become a very important tool of modern political communication. Political parties use it for a variety of purposes, including relationships with its supporters and potential voters. Therefore, the website of any political party is an important channel of communication. Such a website should be user-friendly to various audiences. The purpose of the article is to assess the quality of information architecture (IA) on the websites of the two major American political parties: the Republican Party and the Democratic Party. Triangulation of methods was used in the research: a qualitative-heuristic assessment of the IA on the mentioned websites, expert assessment and a comparative analysis. Within the examined websites, there is a noticeable lack of some important components of the IA. The website of the Republican Party is slightly better in terms of quality than the website of Democratic Party by 14.09%. The results of the conducted research may have an impact not only on the assessment of the technological advancement of parties but also on the image and public perception, and therefore also the effectiveness in reaching voters of a given party. This approach should contribute to the development of websites research in order to improve the quality of user experience and information processes.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135980884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0