Мақаланы E-mail арқылы жіберу An analysis of intelligent methods and algorithms for unlabeled data processing
- Авторлар: Engel EА1, Engel' E.A.1
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Мекемелер:
- Шығарылым: Том 12, № 2 (2011)
- Беттер: 92-96
- Бөлім: Articles
- URL: https://journals.eco-vector.com/2712-8970/article/view/505744
- ID: 505744
Дәйексөз келтіру
Толық мәтін
Аннотация
Intelligent algorithms and method is well-suited to many problems in data processing, where unlabeled data may
be abundant. We survey previously used selection strategies for intelligent model, and propose two novel algorithms
to address their shortcomings, focus on Active Learning (AL). While has already been shown to markedly reduce
the annotation efforts for many sequence labeling tasks compared to random selection, AL remains unconcerned about
the internal structure of the selected sequences (typically, sentences). We propose a semi-supervised AL approach
for sequence labeling.
be abundant. We survey previously used selection strategies for intelligent model, and propose two novel algorithms
to address their shortcomings, focus on Active Learning (AL). While has already been shown to markedly reduce
the annotation efforts for many sequence labeling tasks compared to random selection, AL remains unconcerned about
the internal structure of the selected sequences (typically, sentences). We propose a semi-supervised AL approach
for sequence labeling.
Негізгі сөздер
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