Semi-Supervised Morphosyntactic Classification of Old Icelandic
نویسندگان
چکیده
منابع مشابه
Semi-Supervised Morphosyntactic Classification of Old Icelandic
We present IceMorph, a semi-supervised morphosyntactic analyzer of Old Icelandic. In addition to machine-read corpora and dictionaries, it applies a small set of declension prototypes to map corpus words to dictionary entries. A web-based GUI allows expert users to modify and augment data through an online process. A machine learning module incorporates prototype data, edit-distance metrics, an...
متن کاملDetecting Concept Drift in Data Stream Using Semi-Supervised Classification
Data stream is a sequence of data generated from various information sources at a high speed and high volume. Classifying data streams faces the three challenges of unlimited length, online processing, and concept drift. In related research, to meet the challenge of unlimited stream length, commonly the stream is divided into fixed size windows or gradual forgetting is used. Concept drift refer...
متن کاملOn Semi-Supervised Classification
A graph-based prior is proposed for parametric semi-supervised classification. The prior utilizes both labelled and unlabelled data; it also integrates features from multiple views of a given sample (e.g., multiple sensors), thus implementing a Bayesian form of co-training. An EM algorithm for training the classifier automatically adjusts the tradeoff between the contributions of: (a) the label...
متن کاملSemi-Stacking for Semi-supervised Sentiment Classification
In this paper, we address semi-supervised sentiment learning via semi-stacking, which integrates two or more semi-supervised learning algorithms from an ensemble learning perspective. Specifically, we apply metalearning to predict the unlabeled data given the outputs from the member algorithms and propose N-fold cross validation to guarantee a suitable size of the data for training the meta-cla...
متن کاملSemi-Supervised Classification with Universum
The Universum data, defined as a collection of ”nonexamples” that do not belong to any class of interest, have been shown to encode some prior knowledge by representing meaningful concepts in the same domain as the problem at hand. In this paper, we address a novel semi-supervised classification problem, called semi-supervised Universum, that can simultaneously utilize the labeled data, unlabel...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: PLoS ONE
سال: 2014
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0102366