Results 1 - 10
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20
Generating overview summaries of ongoing email thread discussions
- In Proceedings of COLING 2004
, 2004
"... The tedious task of responding to a backlog of email is one which is familiar to many researchers. As a subset of email management, we address the problem of constructing a summary of email discussions. Specifically, we examine ongoing discussions which will ultimately culminate in a consensus in a ..."
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Cited by 25 (0 self)
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The tedious task of responding to a backlog of email is one which is familiar to many researchers. As a subset of email management, we address the problem of constructing a summary of email discussions. Specifically, we examine ongoing discussions which will ultimately culminate in a consensus in a decision-making process. Our summary provides a snapshot of the current stateof-affairs of the discussion and facilitates a speedy response from the user, who might be the bottleneck in some matter being resolved. We present a method which uses the structure of the thread dialogue and word vector techniques to determine which sentence in the thread should be extracted as the main issue. Our solution successfully identifies the sentence containing the issue of the thread being discussed, potentially more informative than subject line. 1
Summarizing email threads
- In Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics (NAACL) Short Paper Section
, 2004
"... Summarizing threads of email is different from summarizing other types of written communication as it has an inherent dialog structure. We present initial research which shows that sentence extraction techniques can work for email threads as well, but profit from email-specific features. In addition ..."
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Cited by 24 (1 self)
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Summarizing threads of email is different from summarizing other types of written communication as it has an inherent dialog structure. We present initial research which shows that sentence extraction techniques can work for email threads as well, but profit from email-specific features. In addition, the presentation of the summary should take into account the dialogic structure of email communication. 1
Summarizing email conversations with clue words
- In Proc. of ACM WWW 07
, 2007
"... Accessing an ever increasing number of emails, possibly on small mobile devices, has become a major problem for many users. Email summarization is a promising way to solve this problem. In this paper, we propose a new framework for email summarization. One novelty is to use a fragment quotation grap ..."
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Cited by 23 (6 self)
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Accessing an ever increasing number of emails, possibly on small mobile devices, has become a major problem for many users. Email summarization is a promising way to solve this problem. In this paper, we propose a new framework for email summarization. One novelty is to use a fragment quotation graph to try to capture an email conversation. The second novelty is to use clue words to measure the importance of sentences in conversation summarization. Based on clue words and their scores, we propose a method called CWS, which is capable of producing a summary of any length as requested by the user. We provide a comprehensive comparison of CWS with various existing methods on the Enron data set. Preliminary results suggest that CWS provides better summaries than existing methods.
Detection of question-answer pairs in email conversations
- In Proceedings of Coling 2004
, 2004
"... While sentence extraction as an approach to summarization has been shown to work in documents of certain genres, because of the conversational nature of email communication where utterances are made in relation to one made previously, sentence extraction may not capture the necessary segments of dia ..."
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Cited by 14 (0 self)
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While sentence extraction as an approach to summarization has been shown to work in documents of certain genres, because of the conversational nature of email communication where utterances are made in relation to one made previously, sentence extraction may not capture the necessary segments of dialogue that would make a summary coherent. In this paper, we present our work on the detection of questionanswer pairs in an email conversation for the task of email summarization. We show that various features based on the structure of emailthreads can be used to improve upon lexical similarity of discourse segments for questionanswer pairing. 1
Digesting virtual ”geek” culture: The summarization of technical internet relay chats
- PROCEEDINGS OF ACL 2005
, 2005
"... This paper describes a summarization system for technical chats and emails on the Linux kernel. To reflect the complexity and sophistication of the discussions, they are clustered according to subtopic structure on the sub-message level, and immediate responding pairs are identified through machine ..."
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Cited by 13 (0 self)
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This paper describes a summarization system for technical chats and emails on the Linux kernel. To reflect the complexity and sophistication of the discussions, they are clustered according to subtopic structure on the sub-message level, and immediate responding pairs are identified through machine learning methods. A resulting summary consists of one or more mini-summaries, each on a subtopic from the discussion.
Discovering frequent work procedures from resource connections
- In Proc.ofIUI-09: Proceedings of the 13th international conference on Intelligent user interfaces
, 2009
"... Intelligent desktop assistants could provide more help for users if they could learn models of the users ’ workflows. However, discovering desktop workflows is difficult because they unfold over extended periods of time (days or weeks) and they are interleaved with many other workflows because of us ..."
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Cited by 5 (2 self)
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Intelligent desktop assistants could provide more help for users if they could learn models of the users ’ workflows. However, discovering desktop workflows is difficult because they unfold over extended periods of time (days or weeks) and they are interleaved with many other workflows because of user multi-tasking. This paper describes an approach to discovering desktop workflows based on rich instrumentation of information flow actions such as copy/paste, SaveAs, file copy, attach file to email message, and save attachment. These actions allow us to construct a graph whose nodes are files, email messages, and web pages and whose edges are these information flow actions. A class of workflows that we call work procedures can be discovered by applying graph mining algorithms to find frequent subgraphs. This paper describes an algorithm for mining frequent closed connected subgraphs and then describes the results of applying this method to data collected from a group of real users. ACM Classification Keywords
Learning-based summarisation of XML documents
, 2007
"... Documents formatted in eXtensible Markup Language (XML) are available in collections of various document types. In this paper, we present an approach for the summarisation of XML documents. The novelty of this approach lies in that it is based on features not only from the content of documents, but ..."
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Cited by 5 (0 self)
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Documents formatted in eXtensible Markup Language (XML) are available in collections of various document types. In this paper, we present an approach for the summarisation of XML documents. The novelty of this approach lies in that it is based on features not only from the content of documents, but also from their logical structure. We follow a machine learning, sentence extractionbased summarisation technique. To find which features are more effective for producing summaries, this approach views sentence extraction as an ordering task. We evaluated our summarisation model using the INEX and SUMMAC datasets. The results demonstrate that the inclusion of features from the logical structure of documents increases the effectiveness of the summariser, and that the learnable system is also effective and well-suited to the task of summarisation in the context of XML documents. Our approach is generic, and is therefore applicable, apart from entire documents, to elements of varying granularity within the XML tree. We view these results as a step towards the intelligent summarisation of XML documents.
Scalable discovery of hidden emails from large folders
- In ACM SIGKDD’05
, 2005
"... The popularity of email has triggered researchers to look for ways to help users better organize the enormous amount of information stored in their email folders. One challenge that has not been studied extensively in text mining is the identification and reconstruction of hidden emails. A hidden em ..."
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Cited by 5 (3 self)
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The popularity of email has triggered researchers to look for ways to help users better organize the enormous amount of information stored in their email folders. One challenge that has not been studied extensively in text mining is the identification and reconstruction of hidden emails. A hidden email is an original email that has been quoted in at least one email in a folder, but does not present itself in the same folder. It may have been (un)intentionally deleted or may never have been received. The discovery and reconstruction of hidden emails is critical for many applications including email classification, summarization and forensics. This paper proposes a framework for reconstructing hidden emails using the embedded quotations found in messages further down the thread hierarchy. We evaluate the robustness and scalability of our framework by using the Enron public email corpus. Our experiments show that hidden emails exist widely in that corpus and also that our optimization techniques are effective in processing large email folders.
Single-document and Multidocument Summarization Techniques for Email Threads Using Sentence Compression
- In Information Processing and Management: an International Journal, Volume 44, Issue 4
, 2008
"... We present two approaches to email thread summarization: Collective Message Summarization (CMS) applies a multi-document summarization approach, while Individual Message Summarization (IMS) treats the problem as a sequence of single-document summarization tasks. Both approaches are implemented in ou ..."
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Cited by 5 (0 self)
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We present two approaches to email thread summarization: Collective Message Summarization (CMS) applies a multi-document summarization approach, while Individual Message Summarization (IMS) treats the problem as a sequence of single-document summarization tasks. Both approaches are implemented in our general framework driven by sentence compression. Instead of a purely extractive approach, we employ linguistic and statistical methods to generate multiple compressions, and then select from those candidates to produce a final summary. We demonstrate these ideas on the Enron collection—a very challenging corpus because of the highly technical language. Experimental results point to two findings: that CMS represents a better approach to email thread summarization, and that current sentence compression techniques do not improve summarization performance in this genre. 1
Lessons from the ReMail prototypes
- Proc CSCW
, 2004
"... Electronic mail has become the most widely-used application for business productivity and communication, yet many people are frustrated with their email. Though email usage has changed, our email clients largely have not. In this paper, we describe a prototype email client developed out of a multi-y ..."
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Cited by 3 (0 self)
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Electronic mail has become the most widely-used application for business productivity and communication, yet many people are frustrated with their email. Though email usage has changed, our email clients largely have not. In this paper, we describe a prototype email client developed out of a multi-year iterative design process aimed at providing those who “live in their email” with an improved, integrated email experience. We highlight innovative features and describe the user trials for each version of the prototype with resulting modifications. Finally, we discuss how these studies have recast our understanding of the email “habitat ” and user needs.

