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  1. Proceedings of the 2013 international workshop on Mining unstructured big data using natural language processing (UnstructureNLP '13)
  2. Exploiting topic tracking in real-time tweet streams
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Big data opportunities and challenges for IR, text mining and NLP
Mining semantics for culturomics: towards a knowledge-based approach
Information fusion in taxonomic descriptions
Analyzing future communities in growing citation networks
Review rating prediction based on the content and weighting strong social relation of reviewers
Exploiting topic tracking in real-time tweet streams
Sentiment analysis of sentences with modalities
Are words enough?: a study on text-based representations and retrieval models for linking pins to online shops
Says who?: automatic text-based content analysis of television news
Mirroring the real world in social media: twitter, geolocation, and sentiment analysis

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Exploiting topic tracking in real-time tweet streams

Content Provider ACM Digital Library
Author Fei, Yue Hong, Yihong Yang, Jianwu
Abstract Microblogs such as Twitter have become an increasingly popular source of real-time information.Users tend to keep up-to-date with the developments of topics they are interested in. In this paper, we present an effective real-time tweets filtering system to exploit topic tracking in social media streams. We combine background corpus with foreground corpus to handle the cold start problem. Then we build the Content Model to describe the characteristics of tweets, in which we utilize the link information to expand tweets' content aiming at enriching the semantic information of tweets, and we also analyze the influence of tweet's quality measured by a group of well-defined symbols. Moreover, the Pseudo Relevance Feedback approach triggered by a fixed-width temporal sliding window is employed to adapt our system to the alteration of topics over time. Experimental results on Tweet11 corpus indicate that our system achieves good performance in both T11SU and F-0.5 metrics, and the proposed system has better performance than the best one of TREC2012 real-time filtering pilot task.
Starting Page 31
Ending Page 38
Page Count 8
File Format PDF
ISBN 9781450324151
DOI 10.1145/2513549.2513555
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2013-10-28
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Topic tracking Twitter Real-time filtering
Content Type Text
Resource Type Article
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