Automatic summarization of reader comments in on-line news is a challenging but clearly useful task. Work to date has produced extractive summaries using well-known techniques from other areas of NLP. But do users really want these, and do they support users in realistic tasks? We specify an alternative summary type for reader comments, based on the notions of issues and viewpoints, and demonstrate our user interface to present it. An evaluation to assess how well summarization systems support users in time-limited tasks (identifying issues and characterizing opinions) gives good results for this prototype
The volume of data on the social media is huge and even keeps increasing. The need for efficient pro...
Automatic text summarization is a particularly challenging Natural Language Processing (NLP) task in...
In this paper we address extractive summarization of long threads in online discussion fora. We pres...
Researchers are beginning to explore how to generate summaries of extended argumentative conversat...
The abundance of social media platforms and other traditional types of websites allowing their users...
Readers of a news article often read its comments contributed by other readers. By reading comments,...
User commenting is a valuable feature of many news outlets, enabling them a contact with readers and...
Newsrooms are still searching for ways to manage user comments because of both a desire for professi...
We examined whether the microblog comments given by people after reading a web document could be exp...
In neural abstractive summarization field, conventional sequence-to-sequence based models often suff...
Comments left by readers on Web documents contain valu-able information that can be utilized in diff...
Text summarization has emerged as an increasingly established field over the course of the past ten ...
An increasing number of Web applications are allowing users to play more active roles for enriching ...
PACLIC 21 / Seoul National University, Seoul, Korea / November 1-3, 2007conference pape
This work investigates summarizing the conversations that occur in the comments section of the UK ne...
The volume of data on the social media is huge and even keeps increasing. The need for efficient pro...
Automatic text summarization is a particularly challenging Natural Language Processing (NLP) task in...
In this paper we address extractive summarization of long threads in online discussion fora. We pres...
Researchers are beginning to explore how to generate summaries of extended argumentative conversat...
The abundance of social media platforms and other traditional types of websites allowing their users...
Readers of a news article often read its comments contributed by other readers. By reading comments,...
User commenting is a valuable feature of many news outlets, enabling them a contact with readers and...
Newsrooms are still searching for ways to manage user comments because of both a desire for professi...
We examined whether the microblog comments given by people after reading a web document could be exp...
In neural abstractive summarization field, conventional sequence-to-sequence based models often suff...
Comments left by readers on Web documents contain valu-able information that can be utilized in diff...
Text summarization has emerged as an increasingly established field over the course of the past ten ...
An increasing number of Web applications are allowing users to play more active roles for enriching ...
PACLIC 21 / Seoul National University, Seoul, Korea / November 1-3, 2007conference pape
This work investigates summarizing the conversations that occur in the comments section of the UK ne...
The volume of data on the social media is huge and even keeps increasing. The need for efficient pro...
Automatic text summarization is a particularly challenging Natural Language Processing (NLP) task in...
In this paper we address extractive summarization of long threads in online discussion fora. We pres...