You've Got Email: A Workflow Management Extraction System

Email is one of the most powerful tools for communication. Many businesses use email as the main channel for communication, so it is possible that substantial data are included in email content. In order to help businesses grow faster, a workflow management system may be required. The data gathered from email content might be a robust source for a workflow management system. This research proposes an email extraction system to extract data from any incoming emails into suitable database fields. The database, which is created by the program, has been planned for the implementation of a workflow management system. The research is presented in three phases: (1) define suitable criteria to extract data; (2) implement a program to extract data, and store them in a database; and (3) implement a program for validating data in a database. Four criteria are applied for an email extraction system. The first criterion is to select contact information at the end of the email content; the second criterion is to select specified keywords, such as tel, email, and mobile; the third criterion is to select unique names, which start with a capital letter, such as the names of people, places, and corporates; the fourth criterion is to select special texts, such as Co. Ltd, .com, and www. The empirical results suggest that when all four criteria are considered, the accuracy of a program and percentage of blank fields are at an acceptable level compared with the results from other criteria. When four criteria are applied to extract 7,340 emails in English, the accuracy of this experiment is approximately 68.66%, while the percentage of blank fields in a database is approximately 68.05. The database created by the experiment can be applied in a workflow management system

Using conditional random fields to extract contexts and answers of questions from online forums

Online forum discussions often contain vast amounts of questions that are the focuses of discussions. Extracting contexts and answers together with the questions will yield not only a coherent forum summary but also a valuable QA knowledge base. In this paper, we propose a general framework based on Conditional Random Fields (CRFs) to detect the contexts and answers of questions from forum threads. We improve the basic framework by Skip-chain CRFs and 2D CRFs to better accommodate the features of forums for better performance. Experimental results show that our techniques are very promising.

Smart To-Do : Automatic Generation of To-Do Items from Emails

Intelligent features in email service applications aim to increase productivity by helping people organize their folders, compose their emails and respond to pending tasks. In this work, we explore a new application, Smart-To-Do, that helps users with task management over emails. We introduce a new task and dataset for automatically generating To-Do items from emails where the sender has promised to perform an action. We design a two-stage process leveraging recent advances in neural text generation and sequence-to-sequence learning, obtaining BLEU and ROUGE scores of 0:23 and 0:63 for this task. To the best of our knowledge, this is the first work to address the problem of composing To-Do items from emails.Comment: 58th annual meeting of the Association for Computational Linguistics (ACL), 202

Trying On—Being In—Becoming: Four Women’s Journey(s) in Feminist Poststructural Theory

This is the narrative of four women in academia spanning a ten-year relational journey. As a performance collaborative autoethnography, it explores and presents theories of subjectivity and transitional space. Through journals, emails, and dialogue we are trying on, being in, and becoming feminist poststructural thinkers/inquirers/teacher educators. In our work, we explore: How has theory changed our subjectivity, lived experiences and relationships, and moved us from comfortable spaces of knowing to uncomfortable places of becoming? In a series of poetry and performance narratives, we chart our own linked journey(s) in pursuing these questions. As autoethnographers, we grapple with meanings and moments of loss, desire, guilt, and love as a practice of hypomnemata. This study represents a reflective mining of such treasures, capturing moments of rereading and meditation, and a pause, even if an illusionary one, in our intellectual, spiritual, emotional, and embodied journey(s). Our work illustrates how the self looks in transitional space: in motion, contemporaneous, simultaneously in the making and in relation to others. We continue this practice as a pedagogy for being and living out the fictions of our lives

Automatic Summarization

It has now been 50 years since the publication of Luhn’s seminal paper on automatic summarization. During these years the practical need for automatic summarization has become increasingly urgent and numerous papers have been published on the topic. As a result, it has become harder to find a single reference that gives an overview of past efforts or a complete view of summarization tasks and necessary system components. This article attempts to fill this void by providing a comprehensive overview of research in summarization, including the more traditional efforts in sentence extraction as well as the most novel recent approaches for determining important content, for domain and genre specific summarization and for evaluation of summarization. We also discuss the challenges that remain open, in particular the need for language generation and deeper semantic understanding of language that would be necessary for future advances in the field