Proceedings of the 14th International Conference on Management of Digital EcoSystems最新文献

Are Altmetrics Useful for Assessing Scientific Impact?: A Survey 替代指标对评估科学影响有用吗?:调查

Proceedings of the 14th International Conference on Management of Digital EcoSystems Pub Date : 2022-10-19 DOI: 10.1145/3508397.3564845

Yusra Shakeel, Rand Alchokr, J. Krüger, Thomas Leich, Gunter Saake

{"title":"Are Altmetrics Useful for Assessing Scientific Impact?: A Survey","authors":"Yusra Shakeel, Rand Alchokr, J. Krüger, Thomas Leich, Gunter Saake","doi":"10.1145/3508397.3564845","DOIUrl":"https://doi.org/10.1145/3508397.3564845","url":null,"abstract":"The rapidly expanding corpus of scientific publications poses various types of challenges for researchers, mostly concerning the selection and assessment of publications relevant to their research topic. Therefore, the scientific community is actively involved in proposing solutions for effectively retrieving promising publications. Traditional bibliometrics, such as citations, are most commonly used for evaluating the research impact of a publication, in spite of rightful criticism. More recently, the newly introduced altmetrics (e.g., Tweets) have gained popularity and are constantly being investigated to understand their usefulness and potential benefits for assessing the significance of publications. Researchers argue that altmetrics can be used to reflect the importance of a publication beyond the boundaries of traditional bibliometrics. However, it is important to be aware of the limitations and threats arising from altmetrics, too. In this paper, we present a survey analysis to understand the usefulness of altmetrics and determine their ability of being used as quality indicators for scientific research. Based on the findings, we discuss whether altmetrics can support the quality assessment during literature analyses to assist the analyst by reducing the required time and manual effort.","PeriodicalId":266269,"journal":{"name":"Proceedings of the 14th International Conference on Management of Digital EcoSystems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115696792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Novel Approach to Populate Multimedia Knowledge Graph via Deep Learning and Semantic Analysis 一种基于深度学习和语义分析的多媒体知识图谱填充方法

Proceedings of the 14th International Conference on Management of Digital EcoSystems Pub Date : 2022-10-19 DOI: 10.1145/3508397.3564846

A. M. Rinaldi, Cristiano Russo, Cristian Tommasino

引用次数: 1

Graphene Detection System 石墨烯检测系统

Proceedings of the 14th International Conference on Management of Digital EcoSystems Pub Date : 2022-10-19 DOI: 10.1145/3508397.3564850

S. Balasubramaniyan, M. Thévenin, F. Amiel, M. Trocan

{"title":"Graphene Detection System","authors":"S. Balasubramaniyan, M. Thévenin, F. Amiel, M. Trocan","doi":"10.1145/3508397.3564850","DOIUrl":"https://doi.org/10.1145/3508397.3564850","url":null,"abstract":"Ever since the first isolation of graphene, the semimetal has grown appreciable and has been attracting increasing interest. This interest is reinforced by monolayer graphene's remarkable electronic properties and its usage in revolutionary device developments and applications. However, obtaining monolayer graphene which can be deployed for expansion of experiments in 2D physics comes with its own limitations like high human interventions that requires significant experience, is highly time consuming since it involves repetitive tasks and recognizing graphene crystallites from millions of thicker graphite flakes with other undesired particles is strenuous. Here, we report an approach to detect and discriminate monolayer graphene from other alternating layers of graphene and subsisting substrate impurities. We present a region of interest-based image segmentation process to extricate inapplicable information from the image and extract graphene particles. We, then apply an intensity-based detection model leveraging the characteristic color information to differentiate monolayer graphene from other particles and it is observed that the red color space of the monolayer graphene differs 1.8--6%, green 2.5--8% and blue differ 2.5% to 3% from the surrounding background pixels. We also describe an implementation of our algorithm in a semi-automatic system suitable with our needs.","PeriodicalId":266269,"journal":{"name":"Proceedings of the 14th International Conference on Management of Digital EcoSystems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121141066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IdSM-O: An IoT Data Sharing Management Ontology for Data Governance IdSM-O:面向数据治理的物联网数据共享管理本体

Proceedings of the 14th International Conference on Management of Digital EcoSystems Pub Date : 2022-10-19 DOI: 10.1145/3508397.3564825

Nouha Laamech, M. Munier, C. Pham

{"title":"IdSM-O: An IoT Data Sharing Management Ontology for Data Governance","authors":"Nouha Laamech, M. Munier, C. Pham","doi":"10.1145/3508397.3564825","DOIUrl":"https://doi.org/10.1145/3508397.3564825","url":null,"abstract":"The main purpose of IoT is to deliver reliable, high quality services and innovative solutions by transforming the captured data into meaningful information, and thus improving user's daily life. In this regard, it is in the interest of the community to encourage entities within IoT environments to share their data, and therefore serve public interest and contribute to the innovation and technological progress. Meanwhile, the distributed nature of IoT networks and the diversity of its actors lead to the recognition of security and data sharing management as one of the major challenges of the IoT domain. For instance, due to insufficient governance of the shared data within IoT environments, data provider retains little to no control over his assets once he has agreed to share them. Furthermore, data consumers are not able to trace the source of the available resource nor its history processing to assess its quality. All this creates a digital environment that is certainly functional but lacks mutual trust between its actors, which can prevent the domain's full potential to be exploited, and therefore disrupt the implemented services. In our work, we propose an approach to improve data sharing management using three main elements: semantic modeling, usage control policies, and data provenance.","PeriodicalId":266269,"journal":{"name":"Proceedings of the 14th International Conference on Management of Digital EcoSystems","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133411556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Business Insights Using Knowledge Graphs by Text Analytics in Dynamic Environments 通过文本分析在动态环境中使用知识图谱的业务洞察

Proceedings of the 14th International Conference on Management of Digital EcoSystems Pub Date : 2022-10-19 DOI: 10.1145/3508397.3564833

Muhammad Arslan, C. Cruz

{"title":"Business Insights Using Knowledge Graphs by Text Analytics in Dynamic Environments","authors":"Muhammad Arslan, C. Cruz","doi":"10.1145/3508397.3564833","DOIUrl":"https://doi.org/10.1145/3508397.3564833","url":null,"abstract":"Business Intelligence (BI) requires the collection and organization of important pieces of information (i.e. entities) from multiple sources to provide valuable insights (e.g. business trends) as events (i.e. a specific happening linked with a specific location and time) to users. Online news articles are one of the important information sources that present business news offered by various companies in the market every day all around the world. These news articles often cover the same events and report redundant information. Existing news platforms aim at collecting the key entities from news articles and providing a mechanism to view the latest and relevant business events based on user interest. However, they do not provide a method to model business events and understand them temporally, spatially, and contextually (i.e. changes in the event). For instance, it is crucial to know for how long a business event has been active? How important is its evolution locally, or worldwide? Or how did different companies come up with this event as competitors in the market? The contribution of this research is the exploration of the possibilities of modeling spatial, temporal, and contextual information evolution related to business events through the application of knowledge graphs and text analytics, more specifically, Natural Language Processing (NLP) methods. The constructed knowledge graphs through Named-Entity Recognition (NER), i.e., an NLP technique, present a compact news representation that tells the key entities of the business event at one glance using linked open data concepts. It enables the assessment of other related news events as well as provides the means for analysis of the influence and evolution of business events.","PeriodicalId":266269,"journal":{"name":"Proceedings of the 14th International Conference on Management of Digital EcoSystems","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116533384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Learn2Sum: A New Approach to Unsupervised Text Summarization Based on Topic Modeling Learn2Sum:一种基于主题建模的无监督文本摘要方法

Proceedings of the 14th International Conference on Management of Digital EcoSystems Pub Date : 2022-10-19 DOI: 10.1145/3508397.3564853

Amal Beldi, S. Sassi, A. Jemai

{"title":"Learn2Sum: A New Approach to Unsupervised Text Summarization Based on Topic Modeling","authors":"Amal Beldi, S. Sassi, A. Jemai","doi":"10.1145/3508397.3564853","DOIUrl":"https://doi.org/10.1145/3508397.3564853","url":null,"abstract":"Due to the enormous volume of data on the web, it is hard for the user to retrieve effective and useful information within the right time. Thus, it has become a need to generate a brief summary from a large amount of textual data according to the user profile. In this context, text summarization is used to identify important information within text documents. It aims to generate shorter versions of the source text, by including only the relevant and salient information. In recent years, the research on summarization techniques based on topic modeling techniques has become a hot topic among researchers thanks to their ability to classify, understand a large text corpora and extract important topics on the text. However, existing studies do not provide the support of personalization when generating summaries because they need to know not only which documents are most helpful to the users, but also which topics and keywords are more or less related to the user' interests. Thus, existing studies lack of the support of adaptive user modeling for user applications in the emerging areas of automatic summarization, topic modeling and visualization. In this context, we propose a new approach of automated text summarization based on topic modeling techniques and taking into account the user's profile which helps to semantically extract relevant topics of textual documents, summarizing information according to the user' topics interests and finally visualize them through a hyper-graph Experiments have been conducted to measure the effectiveness of our solution compared to existing summarizing approaches based on text content. The results show the superiority of our approach.","PeriodicalId":266269,"journal":{"name":"Proceedings of the 14th International Conference on Management of Digital EcoSystems","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127351594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Multiple-Path Routing Model for Quality of Service in Software Defined Networking 软件定义网络中服务质量的多路径路由模型

Proceedings of the 14th International Conference on Management of Digital EcoSystems Pub Date : 2022-10-19 DOI: 10.1145/3508397.3564841

Himanshi Babbar, Shalli Rani, Aman Singh, G. Gianini

引用次数: 0

Towards Anomaly Detection for Monitoring Power Consumption in HPC Facilities 基于异常检测的高性能计算设备功耗监测

Proceedings of the 14th International Conference on Management of Digital EcoSystems Pub Date : 2022-10-19 DOI: 10.1145/3508397.3564826

Nitin Sukhija, Elizabeth Bautista, Drake Butz, C. Whitney

{"title":"Towards Anomaly Detection for Monitoring Power Consumption in HPC Facilities","authors":"Nitin Sukhija, Elizabeth Bautista, Drake Butz, C. Whitney","doi":"10.1145/3508397.3564826","DOIUrl":"https://doi.org/10.1145/3508397.3564826","url":null,"abstract":"Given the increasing complexity and the heterogeneity of today's computing system infrastructure, power efficiency and fault tolerance remain the top challenges of an High Performance Computing (HPC) facility operation. Recently, many research efforts are focusing on monitoring solutions for collecting, correlating, and analyzing computing infrastructures health events and metrics data to not only identify the normal events but also the anomalous, thus aiding to reduce downtime and power consumption in the face of a computational center's and users' critical needs. In this preliminary work, we present an anomaly detection methodology integrated with the Operations Monitoring and Notification Infrastructure (OMNI) data warehouse at Lawrence Berkeley National Laboratory's (LBNL) National Energy Scientific Computing Center (NERSC) that has implemented anomaly detection algorithms for identifying abnormal power patterns. We evaluated our methodology using five million unlabeled power datasets from the Cori computation system at NERSC and reported on the accuracy of the anomaly detection algorithms in detecting different anomalous behavior pertaining to the amount of power consumed. The methodology is employed to aid in monitoring and automating power alerting to achieve power efficiency and reliability in future systems to be deployed at NERSC or other HPC facilities.","PeriodicalId":266269,"journal":{"name":"Proceedings of the 14th International Conference on Management of Digital EcoSystems","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123304686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Aspect-Based Sentiment Analysis of Arabic Restaurants Customers' Reviews Using a Hybrid Approach 基于方面的阿拉伯餐厅顾客评论情感分析

Proceedings of the 14th International Conference on Management of Digital EcoSystems Pub Date : 2022-10-19 DOI: 10.1145/3508397.3564834

Faris Al-Smadi, B. Al-Shboul, Duha Al-Darras, D. A. Qudah

{"title":"Aspect-Based Sentiment Analysis of Arabic Restaurants Customers' Reviews Using a Hybrid Approach","authors":"Faris Al-Smadi, B. Al-Shboul, Duha Al-Darras, D. A. Qudah","doi":"10.1145/3508397.3564834","DOIUrl":"https://doi.org/10.1145/3508397.3564834","url":null,"abstract":"In this study, an Aspect-based Sentiment Analysis (ABSA) model was developed to classify restaurants' reviews in the Arabic language based on four predefined aspects: price, cleanliness, food quality, and service. A hybrid approach that combines machine learning with domain-specific dictionaries and sentiment word lists was proposed for ABSA. More than 3,000 reviews were collected from a restaurant reviews website. The reviews were annotated using a crowdsourcing method. The annotated reviews were pre-processed, then the dictionaries and sentiment word lists were extracted from the dataset. Moreover, a filter-based feature selection approach using the Chi2 method was applied to reduce the number of representative features. Four aspect models were built using Support Vector Machine (SVM) and another four models were built using Naïve Bayes (NB) classifiers, one model for each aspect. The models were evaluated using Accuracy, Precision, Recall, and F-Measure. The results were promising, as the price aspect model achieved the highest results by applying the SVM classifier with Accuracy 84.47%, Precision 84.3%, Recall 84.5%, and F-Measure 84.3%.","PeriodicalId":266269,"journal":{"name":"Proceedings of the 14th International Conference on Management of Digital EcoSystems","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117323475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing Business Processes through Parallel Task Execution 通过并行任务执行优化业务流程

Proceedings of the 14th International Conference on Management of Digital EcoSystems Pub Date : 2022-10-19 DOI: 10.1145/3508397.3564842

Konstantinos Varvoutas, Georgia Kougka, A. Gounaris

引用次数: 1