Voting experts: An unsupervised algorithm for segmenting sequences
| Autor: | Paul R. Cohen, Niall M. Adams, Brent Heeringa |
|---|---|
| Rok vydání: | 2007 |
| Předmět: |
Exploit
Computer science business.industry media_common.quotation_subject Pattern recognition Mobile robot Theoretical Computer Science Unsupervised algorithm Market segmentation Artificial Intelligence Voting Data_FILES Entropy (information theory) Computer Vision and Pattern Recognition Artificial intelligence business Formal description media_common |
| Zdroj: | Intelligent Data Analysis. 11:607-625 |
| ISSN: | 1571-4128 1088-467X |
| DOI: | 10.3233/ida-2007-11603 |
| Popis: | We describe a statistical signature of chunks and an algorithm for finding chunks. While there is no formal definition of chunks, they may be reliably identified as configurations with low internal entropy or unpredictability and high entropy at their boundaries. We show that the log frequency of a chunk is a measure of its internal entropy. The Voting-Experts exploits the signature of chunks to find word boundaries in text from four languages and episode boundaries in the activities of a mobile robot. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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