NDLI: Live Semantic Sport Highlight Detection Based on Analyzing Tweets of Twitter

Content Provider	IEEE Xplore Digital Library
Author	Liang-Chi Hsieh Ching-Wei Lee Tzu-Hsuan Chiu Hsu, W.
Copyright Year	2012
Abstract	Microblogging as a new form of communication on Internet, has attracted the attention from researchers recently. Relying the real-time and conversational properties of microblogging, its users update their statuses and share experience within their the social network. Those characteristics also make microblogging an important tool for users to share or discuss real world events such as earth quake or sport game. In this paper, we propose a novel and flexible solution to detect and recognize real-time events from sport games based on analyzing the messages posted on microblogging services. We take Twitter as the experiment platform and collect a large-scale dataset of Twitter messages that are called tweets for 18 prominent sport games covering four types of sports in 2011. We also collect corresponding sport videos for those games. The proposed solution applies moving-threshold burst detection on the volume of tweets to detect highlights in sport games. A tf-idf-based weighting method is applied on the tweets within detected highlights for semantic extraction. According to the experiments we perform on the tweet and video datasets, we find that the proposed methods can achieve competent performance in sport event detection and recognition. Besides, our method can find non pre-defined tidbits that are difficult to detect in previous works.
Starting Page	949
Ending Page	954
File Size	353796
Page Count	6
File Format	PDF
ISBN	9781467316590
ISSN	19457871
DOI	10.1109/ICME.2012.135
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-09
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Games Twitter Videos Event detection Sports equipment Semantics Real time systems burst detection Microblogging event detection
Content Type	Text
Resource Type	Article

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