Paper Info
Title
Towards Effective Extraction and Linking of Software Mentions from User-Generated Support Tickets.
Abstract
Software support tickets contain short and noisy text from the customers. Software products are often represented by various surface forms and informal abbreviations. Automatically identifying software mentions from support tickets and determining the official names and versions are helpful for many downstream applications, \eg routing the support tickets to the right expert groups for support. In this work, we study the problem ofsoftware product name extraction andlinking from support tickets. We first annotate and analyze sampled tickets to understand the language patterns. Next, we design features using local, contextual, and external information sources, for extraction and linking models. In experiments, we show that linear models with the proposed features are able to deliver better and more consistent results, compared with the state-of-the-art baseline models, even on dataset with sparse labels.
Year
DOI
Venue
2018
10.1145/3269206.3272026
CIKM
Keywords
Field
DocType
Support ticket, entity extraction, entity linking
Entity linking,Information retrieval,Computer science,Linear model,Noisy text,Pattern language,Software,Product name
Conference
ISBN
Citations 
PageRank 
978-1-4503-6014-2
2
0.39
References 
Authors
39
4
Name
Order
Citations
PageRank
Jianglei Han131.08
Ka Hian Goh220.39
Aixin Sun33071156.89
Mohammad K. Akbari430121.78