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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Karaoglan, B. Kisla, T. Dincer, B.T. Metin, S.K. |
| Copyright Year | 2013 |
| Description | Author affiliation: Enformatik Bolumu, Mugla Univ., Mugla, Turkey (Dincer, B.T.) || Bilgisayar ve Ogretim Teknolojileri Egitimi Bolumu, Ege Univ., İzmir, Turkey (Kisla, T.) || Yazilim Muhendisligi Bolumu, Izmir Ekonomi Univ., Izmir, Turkey (Metin, S.K.) || Uluslararasi Bilgisayar Enstitusu, Ege Univ., İzmir, Turkey (Karaoglan, B.) |
| Abstract | In order to compare work done under natural language processing, the corpora involved in different studies should be standardized/normalized. Entropy, used as language model performance metric, totally depends on signal information. Whereas, when language is considered semantic information should also be considered. Here we propose a metric that exploits Zipf's and Heaps' power laws to respresent semantic information in terms of signal information and estimates the amount of information anticipated from a corpus of given length in words. The proposed metric is tested on 20 different lengths of sub-corpora drawn from major corpus in Turkish (METU). While the entropy changed depending on the length of the corpus, the value of our proposed metric stayed almost constant which supports our claim about normalizing the corpus. |
| Sponsorship | IEEE Turkey Sect. SP Chapter |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 331053 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781467355629 |
| e-ISBN | 9781467355636 |
| e-ISBN | 9781467355612 |
| DOI | 10.1109/SIU.2013.6531217 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-04-24 |
| Publisher Place | Turkey |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Measurement Computers Presses Semantics cross entropy Educational institutions language model performance Entropy Weaving corpus comparison |
| Content Type | Text |
| Resource Type | Article |
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