Email Management System Research Articles

Design and Development of an Emailing Management System: System Modeling

Developing a software platform that effectively handles email communication is the main goal of creating an email management system. Given the growing importance of electronic communication in various fields, its relevance in today's landscape cannot be overstated. This system encompasses a variety of features designed to streamline the process of sending, monitoring, and organizing emails with the utmost efficiency. Whether it's used for marketing, customer relationship management (CRM), outreach efforts, or internal communication within companies, it offers a comprehensive set of tools to facilitate these tasks seamlessly. Building and maintaining strong customer relationships, generating leads, promoting products or services, and improving an organization's online presence all depend on the presence of a well-designed email management system. In addition, intelligent email management serves to strengthen online reputation and ensure compliance with legal privacy standards. The goal of this effort is to create, refine, and optimize a comprehensive email management system tailored to an organization's unique requirements. Goals include improving the effectiveness of email campaigns, optimizing the successful delivery of messages, complying with privacy regulations, and providing a user-friendly interface. In this work, we will focus on the modeling of the system. UML modeling language is employed to clearly illustrate both static and dynamic aspects of the system, encompassing class, use case, activity, and sequence diagrams. To enhance the tangibility of the proposed solution, we developed four user interface prototypes.

FRONT-END DEVELOPMENT OF WEB-BASED E-MAIL MANAGEMENT SYSTEM IN TELKOM ACCESS KEDATON BANDAR LAMPUNG

The development of information has penetrated into the digital realm, by utilizing computer technology as an information technology tool in an organization or company will provide added value to the data processing process. The process of data processing in the form of incoming and outgoing letters at PT. Telkom Access is still done conventionally as well as manual archiving, with higher correspondence intensity and demands for speed and punctuality. In this study, we will develop a website-based e-mail management system display using the CodeIgniter3 framework and Bootstrap with the scrum methodology. It is hoped that by developing the appearance of the system, it can make it easier and more comfortable for users to use the system.

E-politeness in student requests to faculty: А view from a regional Russian university in the midst of a pandemic

This paper explores pragmalinguistic strategies in the Russian language student requests made to faculty via email and Moodle learning management system (LMS) at Chelyabinsk State University, Russia, from March 2020 to March 2021, in the period of the COVID-19 pandemic restrictions. Drawing from the sample and a questionnaire, we focus on the type of request and its level of imposition, as well as the internal and external modification, following a modified Cross-Cultural Study of Speech Act Realization Patterns framework. The reported case study shows that students use LMS for making requests for action, and resort to email to request information. External modification is a dominant strategy used to mitigate the impositive force of the requests in the sample. LMS requests tend to be concise and directed at ‘getting stuff done’ with minimal mitigation strategies. This may illustrate a lack of essential pragmatic competence on the students’ part and be connected to the normalisation of a telegraph-style communication.

Peer review declaration

All papers published in this volume of Journal of Physics: Conference Series have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.• Type of peer review: Single-blind/Double-blind/Triple-blind/Open/Other (please describe) Double-blind • Conference submission management system: Using the conference website and the email management system. • Number of submissions received: 68 • Number of submissions sent for review: 53 • Number of submissions accepted:47 • Acceptance Rate (Number of Submissions Accepted/Number of Submissions Received X 100):69.12% • Average number of reviews per paper: 2 • Total number of reviewers involved:30 reviewers distributed in different countries. • Any additional info on review process: All papers should be revised according to the reviewers’ comments (at least two reviewers) to revise 1-2 times. We design the review form to let the reviewers review papers and write their comments (According to Originality of the Topics, Technical Quality, Importance in Its Fields, Style and Overall Representation, Readily Understandable, Suitability for Journal, Adequate Illustrations or Drawings etc. to write the comments and make the final decisions, such as “Accepted as it is”, “Minor revision”, “Major revision”, “Decline submission [Reject] ”, then we collect two reviewers’ comments into the author response comments table to let the authors fill in the revisions and revise their papers according to the reviewers’ comments. Some papers will send to the third reviewer for confirming the papers for publication or rejection. The selected papers reviewed by at least two reviewers are sent for the publications after the recommendation of the chief editor. • Contact person for queries: Conference Chair : Chair Professor Gow-Yi Tzou, PhDAffiliation:Chung-Chou University of Science and Technologygowyitzou@gm.ccut.edu.tw or johnsontzou@gmail.com

Reply Using Past Replies—A Deep Learning-Based E-Mail Client

Email is the most common and effective source of communication for most enterprises and individuals. In the corporate sector the volume of email received daily is significant while timely reply of each email is important. This generates a huge amount of work for the organisation, in particular for the staff located in the help-desk role. In this paper we present a novel Smart E-mail Management System (SEMS) for handling the issue of E-mail overload. The Term Frequency-Inverse Document Frequency (TF-IDF) model was used for designing a Smart Email Client in previous research. Since TF-IDF does not consider semantics between words, the replies suggested by the model are not very accurate. In this paper we apply Document to Vector (Doc2Vec) and introduce a novel Gated Recurrent Unit Sentence to Vector (GRU-Sent2Vec), which is a hybrid model by combining GRU and Sent2Vec. Both models are more intelligent as compared to TF-IDF. We compare our results from both models with TF-IDF. The Doc2Vec model performs the best on predicting a response for a similar new incoming Email. In our case, since the dataset is too small to require a deep learning algorithm model, the GRU-Sent2Vec hybrid model cannot produce ideal results, whereas in our understanding it is a robust method for long-text prediction.

3372 Developing a REDCap Database to Understand Partnership Cultivation Efforts

OBJECTIVES/SPECIFIC AIMS:.Outline the development and purpose of the partnership brokering database in REDCap. Provide an overview of the tool and how it works. Discuss how this tool facilitates partnership-brokering activities and discuss plans for future use METHODS/STUDY POPULATION: Research Electronic Data Capture (REDCap) is a secure, web-based application developed at Vanderbilt University to assist with systematic data management of small and medium sized projects. CCH utilized REDCap to build a custom data management warehouse entitled the Partnership Brokering Tool. Information compiled in various formats (handwritten notes, spreadsheets, etc.) over the past 10 years by CCH staff, was then systematically organized and entered into the Partnership Brokering Tool. The tool captures information such as individual contact information, organizational affiliation (academic, community, faith, government etc.), research interests (35 categories - asthma, diabetes, heart disease, etc.), communities of foci (children, elderly, LGBTQ, ethnicity, etc.), and target geographic community served (Chicago north, south, suburban, Illinois, etc.). RESULTS/ANTICIPATED RESULTS: Data was compiled on 451 community groups and organizations and 77 partners in academia thus far. Community organizations represent a range of community sectors including advocacy and policy groups, community-based, faith-based organizations, foundations, media, schools, etc. throughout the Chicagoland area. Data analysis activities are underway, however, results will also be shared regarding characteristics of the communities these organizations serve including:. Age range. Special populations (as defined by the CSTI grant). Underrepresented racial and ethnic communities. DISCUSSION/SIGNIFICANCE OF IMPACT: The Partnership Brokering Tool has provided a format for CCH to systematically gather information about the relationships staff have cultivated with community groups and organizations. Unlike an email management system, this REDCap project is highly useful in capturing the parameters of our partner pool, identifying partnership gaps, and matching individuals interested in collaborating with researchers or community organizations that have a particular skill set or research interest. The Partnership Brokering Tool has also facilitated stakeholder engagement dedicated to guiding the centers’ overall goals, objectives, and programming. Finally, utilizing REDCap has streamlined efforts in reporting quantitative and qualitative data about these organizations. In the next phase of this project, CCH will utilize the database to assess the nature of the relationship between CCH and community groups and organizations.

MSPECTRA: Email Management System of The Journal of Clinical and Diagnostic Research

mSPECTRA: Email Management System of The Journal of Clinical and Diagnostic Research

A layered approach: integrating email security with document management processes

Security attacks today are rampant, exceedingly sophisticated and commonplace. Despite their best efforts, security professionals simply aren't able to impede the onslaught of the ever-increasing volume and maliciousness of cyber-attacks. And there are many manifestations of these attacks – bots, exploit kits, phishing, whaling, ransomware and so on. Organisations face many forms of attack, including exploit kits, phishing, whaling, ransomware and so on. But many of them revolve around email scams. Most organisations already deploy email security solutions to protect against malware and ensure business continuity in the event of a breach. But most neglect the next layer of security and fail to implement a document and email management system to house confidential and business-critical information. It is a major oversight, says Roy Russell of Ascertus.

Improving Email Response in an Email Management System Using Natural Language Processing Based Probabilistic Methods

Email based communication over the course of globalization in recent years has transformed into an all-encompassing form of interaction and requires automatic processes to control email correspondence in an environment of increasing email database. Relevance characteristics defining class of email in general includes the topic of thee mail and the sender of the email along with the body of email. Intelligent reply algorithms can be employed in which machine learning methods can accommodate email content using probabilistic methods to classify context and nature of email. This helps in correct selection of template for email reply. Still redundant information can cause errors in classifying an email. Natural Language Processing (NLP) possess potential in optimizing text classification due to its direct relation with language structure. An enhancement is presented in this research to address email management issues by incorporating optimized information extraction for email classification along with generating relevant dictionaries as emails vary in categories and increases in volume. The open hypothesis of this research is that the underlying concept to fan email is communicating a message in form of text. It is observed that NLP techniques improve performance of Intelligent Email Reply algorithm enhancing its ability to classify and generate email responses with minimal errors using probabilistic methods. Improved algorithm is functionally automated with machine learning techniques to assist email users who find it difficult to manage bulk variety of emails.

Anonymous encryption with partial‐order subset delegation and its application in privacy email systems

In privacy-carrying email systems, the authors should guarantee that the email content is confidential and sometimes the sender/receiver identities are hidden. Also, they require that the key generation is flexible and manageable. In this study, first, they propose an anonymous encryption scheme that supports a partial-order subset delegatable ability. The proposed scheme achieves the security properties of confidentiality against adaptive chosen-plaintext attacks, anonymity against adaptive chosen-subset attacks and computational delegation indistinguishability. Secondly, they provide a deployment application of their anonymous encryption in an interdisciplinary group email management system with flexible and fine-grained key delegation. The deployment can achieve the privacy of message confidentiality, receiver anonymity and delegation obliviousness, which has fine-grained security in secure email systems. Finally, they provide an extension for the chosen-ciphertext secure scheme, and discuss the efficiency for decryption and the security level.

A NOVEL EMAIL RESPONSE ALGORITHM FOR EMAIL MANAGEMENT SYSTEMS

Email has been one of the most commonly used tool for communication in the recent years and email management has evolved as a major challenge due to prevailing situation of online email congestion. This study presents a novel algorithm for automatic email response methodology in an Email Management System to minimize email overload. The proposed model uses Bayes classifier to categorize emails into classes and generate suitable replies to these classes using information extraction and template filling. Our research aims to intelligently automate email response using Naïve Bayesian classification and formulate probabilistic dictionaries for accurate information extraction. This research will help in reducing email overload and unavoidable congestion by employing a novel email response architecture for an email management systems.

Kurumsal Bilgi Kaynağı Olarak E-posta Yönetim Sistemleri

Çalışmada, e-posta kullanımı ve yönetimine ilişkin uluslararası koşullar incelenmekte, bu çerçevede Türkiye’de 28 kurum örneğinde gerçekleştirilen anket verileri değerlendirilmektedir. Betimleme yönteminin kullanıldığı çalışmada literatür incelemesi ve anket tekniklerine dayanarak gerekli veriler elde edilmiştir. Araştırmada e-posta kullanımına ilişkin elde edilen verilerin, ilgili alanda sistemler geliştirmeye çalışan araştırmacılara yardımcı olması beklenmektedir. Kurumsal e-posta yönetimine ilişkin temel sorunlar arasında mesajların üretimi, düzenlenmesi, ayıklanması ve uzun süre korunmasını içeren e-posta yönetim sistemlerinin geliştirilmesi yer almaktadır. Ayrıca insan kaynakları, mali ve idari konuların yönetimi ile belge ve arşiv yönetimi çalışmalarını kapsamına alan, içerisine e-posta yönetiminin de dâhil olduğu sistemlerin bütünleştirilmesi güncel araştırma konuları arasındadır.

Efficient E-mail Management System with Bandwidth Reduction and 3-Level Message Prioritization

In this paper, a new e-mail management system is demonstrated in which all messages are prioritized. Each type of priority message is handled with a special method to enhance the efficiency of the proposed e-mail system. Also, a new management technique for user inbox is introduced. In addition, a minor upgrade in TCP (Transmission Control Protocol) message confirmation (ACK) is demonstrated, to reduce the bandwidth consumption. Finally, the network simulator ns-2 is used to evaluate the new proposed e-mail management system. The obtained results show that the proposed system outperforms the traditional ones from points of view of bandwidth, overall system efficiency, packet loss, and delay.

Canadian government agencies develop e-mail management policies

As e-mail has become a widely used communication tool by the Government of Canada (GoC), this article examines current e-mail management policies and system implementation in Canadian government agencies. GoC implemented the Records, Document, and Information Management System (RDIMS) as an integrated system tool for efficient document and records management. RDIMS provides the capability to create, manage, and access information and documents, regardless of ministerial, departmental, or geographic location. GoC presents legal guidance on e-mail management, based on the Access to Information Act, Privacy Act, and Library and Archives of Canada Act. Developing an e-mail management policy promotes an effective capture, management, and retention of e-mail messages.

Off to new shores: conceptual knowledge discovery and processing

In the last years, the main orientation of formal concept analysis (FCA) has turned from mathematics towards computer science. This article provides a review of this new orientation and analyses why and how FCA and computer science attracted each other. It discusses FCA as a knowledge representation formalism using five knowledge representation principles provided by Davis et al. (1993). It then studies how and why mathematics-based researchers got attracted by computer science. We will argue for continuing this trend by integrating the two research areas FCA and ontology engineering. The second part of the article discusses three lines of research which witness the new orientation of FCA: FCA as a conceptual clustering technique and its application for supporting the merging of ontologies; the efficient computation of association rules and the structuring of the results; and the visualization and management of conceptual hierarchies and ontologies including its application in an email management system.