期刊名称：Conference on European Chapter of the Association for Computational Linguistics (EACL)
出版年度：2012
卷号：2012
出版社：ACL Anthology
摘要：Tweets have become a comprehensive repository
for real-time information. However, it
is often hard for users to quickly get information
they are interested in from tweets, owing
to the sheer volume of tweets as well as
their noisy and informal nature. We present
QuickView, an NLP-based tweet search platform
to tackle this issue. Specifically, it exploits
a series of natural language processing
technologies, such as tweet normalization,
named entity recognition, semantic role labeling,
sentiment analysis, tweet classification, to
extract useful information, i.e., named entities,
events, opinions, etc., from a large volume
of tweets. Then, non-noisy tweets, together
with the mined information, are indexed, on
top of which two brand new scenarios are enabled,
i.e., categorized browsing and advanced
search, allowing users to effectively access
either the tweets or fine-grained information
they are interested in.
