Videoclef 2008: Asr Classification based on Wikipedia Categories

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Videoclef 2008: Asr Classification based on Wikipedia Categories
Authors
Jens Kürsten
Daniel Richter
Maximilian Eibl
Publication date
2008
Links
Original

Videoclef 2008: Asr Classification based on Wikipedia Categories - scientific work related to Wikipedia quality published in 2008, written by Jens Kürsten, Daniel Richter and Maximilian Eibl.

Overview

This article describes participation at the VideoCLEF track of the CLEF campaign 2008. Authors designed and implemented a prototype for the classification of the Video ASR data. Authors approach was to regard the task as text classification problem. Authors used terms from Wikipedia categories as training data for text classifiers. For the text classification the Naive-Bayes and kNN classifier from the WEKA toolkit were used. Authors submitted experiments for classification task 1 and 2. For the translation of the feeds to English (translation task) Google’s AJAX language API was used. The evaluation of the classification task showed bad results for experiments with a precision between 10 and 15 percent. These values did not meet expectations. Interestingly, authors could not improve the quality of the classification by using the provided metadata. But at least the created translation of the RSS Feeds was well.

Embed

Wikipedia Quality

Kürsten, Jens; Richter, Daniel; Eibl, Maximilian. (2008). "[[Videoclef 2008: Asr Classification based on Wikipedia Categories]]".

English Wikipedia

{{cite journal |last1=Kürsten |first1=Jens |last2=Richter |first2=Daniel |last3=Eibl |first3=Maximilian |title=Videoclef 2008: Asr Classification based on Wikipedia Categories |date=2008 |url=https://wikipediaquality.com/wiki/Videoclef_2008:_Asr_Classification_based_on_Wikipedia_Categories}}

HTML

Kürsten, Jens; Richter, Daniel; Eibl, Maximilian. (2008). &quot;<a href="https://wikipediaquality.com/wiki/Videoclef_2008:_Asr_Classification_based_on_Wikipedia_Categories">Videoclef 2008: Asr Classification based on Wikipedia Categories</a>&quot;.