Paper Info
Title
Characterizing and Supporting Question Answering in Human-to-Human Communication.
Abstract
Email continues to be one of the most important means of online communication. People spend a significant amount of time sending, reading, searching and responding to email in order to manage tasks, exchange information, etc. In this paper, we focus on information exchange over enterprise email in the form of questions and answers. We study a large scale publicly available email dataset to characterize information exchange via questions and answers in enterprise email. We augment our analysis with a survey to gain insights on the types of questions exchanged, when and how do people get back to them and whether this behavior is adequately supported by existing email management and search functionality. We leverage this understanding to define the task of extracting question/answer pairs from threaded email conversations. We propose a neural network based approach that matches the question to the answer considering comparisons at different levels of granularity. We also show that we can improve the performance by leveraging external data of question and answer pairs. We test our approach using a manually labeled email data collected using a crowd-sourcing annotation study. Our findings have implications for designing email clients and intelligent agents that support question answering and information lookup in email.
Year
DOI
Venue
2018
10.1145/3209978.3210046
SIGIR
Keywords
Field
DocType
Question Answering,Information Exchange in Email,Email Reply Assistance
Email management,Intelligent agent,Question answering,Annotation,Information retrieval,Computer science,Information exchange,Human communication,Artificial neural network
Conference
ISBN
Citations 
PageRank 
978-1-4503-5657-2
1
0.35
References 
Authors
41
5
Name
Order
Citations
PageRank
Xiao Yang140.79
Ahmed Hassan294357.64
Madian Khabsa323718.81
Wei Wang482.60
Miaosen Wang510.69