Synonyms
Document stream processing
Definition
A text stream is a continuously generated series of comments or small text documents. Each comment or text document may be associated with a time stamp indicating when it was produced or received by a certain device or system. Text stream processing refers to real-time extraction of desired information from text streams (through categorizing and clustering documents in text streams, detecting and tracking topics, matching patterns, and discovering events). Streaming text media (e.g., Twitter, WeChat, Facebook, news feeds, etc.) have fresher content with richer attributes and tend to have broader coverage compared to traditional electronic media (e.g., forums, blogs, and web sites). These advantages make them ripe for use in many engaging, innovative, and empowering applications (see Key Applications, below). In contrast to offline text mining, which analyzes a static collection of text documents (see “Text Mining”), text stream processing...
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Banerjee A, Basu S. Topic models over text streams: a study of batch and online unsupervised learning. In: Proceedings of the 7th SIAM International Conference on Data Mining; 2007. p. 437–42.
Bhide M, Chakaravarthy VT, Ramamritham K, Roy P. Keyword search over dynamic categorized information. In: Proceedings of the IEEE International Conference on Data Engineering; 2009. p. 258–69.
Chen C, Li F, Ooi BC, Wu S. TI: an efficient indexing mechanism for real-time search on tweets. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 2011. p. 649–60.
Elkhalifa L, Adaikkalavan R, Chakravarthy S. InfoFilter: a system for expressive pattern specification and detection over text streams. In: Proceedings of the 2005 ACM Symposium on Applied Computing; 2005. p. 1084–8.
Fung GPC, Yu JX, Yu PS, Lu H. Parameter free bursty events detection in text streams. In: Proceedings of the 31st International Conference on Very Large Data Bases; 2005. p. 181–92.
He Q, Chang K, Lim E-P, Zhang J. Bursty feature representation for clustering text streams. In: Proceedings of the 7th SIAM International Conference on Data Mining; 2007. p. 491–6.
Kleinberg J. Bursty and hierarchical structure in streams. Data Min Knowl Disc. 2003;7(4):373–97.
Li R, Wang S, Chang KC-C. Towards social data platform: automatic topic-focused monitor for twitter stream. Proc VLDB Endow. 2013;6(14):1966–77.
Mei Q, Zhai C. Discovering evolutionary theme patterns from text: an exploration of temporal text mining. In: Proceedings of the 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; 2005. p. 198–207.
Mouratidis K, Pang H. An incremental threshold method for continuous text search queries. In: Proceedings of the 25th International Conference on Data Engineering; 2009. p. 1187–90.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media, LLC, part of Springer Nature
About this entry
Cite this entry
Hwang, JH., Labouseur, A.G., Olsen, P.W. (2018). Text Stream Processing. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_80751
Download citation
DOI: https://doi.org/10.1007/978-1-4614-8265-9_80751
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-8266-6
Online ISBN: 978-1-4614-8265-9
eBook Packages: Computer ScienceReference Module Computer Science and Engineering