Advances in Neural Information Processing Systems 5, [NIPS Conference]
Automatic bilingual lexicon acquisition using random indexing of parallel corpora
Natural Language Engineering
Using bag-of-concepts to improve the performance of support vector machines in text categorization
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
SICS: valence annotation based on seeds in word space
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
The automatic creation of literature abstracts
IBM Journal of Research and Development
Event detection in blogs using temporal random indexing
eETTs '09 Proceedings of the Workshop on Events in Emerging Text Types
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This paper discusses the task of tracking mentions of some topically interesting textual entity from a continuously and dynamically changing flow of text, such as a news feed, the output from an Internet crawler or a similar text source -- a task sometimes referred to as buzz monitoring . Standard approaches from the field of information access for identifying salient textual entities are reviewed, and it is argued that the dynamics of buzz monitoring calls for more accomplished analysis mechanisms than the typical text analysis tools provide today. The notion of word space is introduced, and it is argued that word spaces can be used to select the most salient markers for topicality, find associations those observations engender, and that they constitute an attractive foundation for building a representation well suited for the tracking and monitoring of mentions of the entity under consideration.