[PDF][PDF] Supervised and unsupervised machine learning techniques for text document categorization
A Ozgur - Unpublished Master's Thesis, İstanbul: Boğaziçi …, 2004 - Citeseer
… approaches to enhance this task: supervised approach, where pre-defined category labels
are assigned to documents … set of labelled documents; and unsupervised approach, where …
are assigned to documents … set of labelled documents; and unsupervised approach, where …
[PDF][PDF] Automatic text categorization by unsupervised learning
… sentence as what contains pre-defined keywords of the category … In this paper, a document
is assigned to only one category. … We did not use tag information of web documents. And a so-…
is assigned to only one category. … We did not use tag information of web documents. And a so-…
Unsupervised approaches for textual semantic annotation, a survey
… tools doing entity recognition task in a fully automatic or unsupervised manner, … tags web
pages with concepts from a pre-defined concept set without any need for annotated documents…
pages with concepts from a pre-defined concept set without any need for annotated documents…
Semi-supervised clustering techniques for categorization of text documents
Y Yan - 2015 - dr.ntu.edu.sg
… With the help of a small number of class labels or pair-wise … which have already been
pre-defined by a separate process, … cluster assignment in a hard or crisp clustering approach like …
pre-defined by a separate process, … cluster assignment in a hard or crisp clustering approach like …
Towards unsupervised text classification leveraging experts and word embeddings
Z Haj-Yahia, A Sieg, LA Deleris - … of the 57th annual meeting of …, 2019 - aclanthology.org
… an unsupervised approach to classify documents into categories simply described by a label…
described previously, we assign a label to a document by identifying the label to which it is …
described previously, we assign a label to a document by identifying the label to which it is …
[图书][B] Using unlabeled data to improve text classification
KP Nigam - 2001 - search.proquest.com
… into one (or several) of a set of pre-defined topics of interest. … For a specific classification
task, we select the model's … We can think of EM as almost performing unsupervised clus …
task, we select the model's … We can think of EM as almost performing unsupervised clus …
Learning a concept hierarchy from multi-labeled documents
… this unsupervised structure with noisy, human-provided labels… the task of predicting the
words in held-out test documents, … from a set of pre-defined K labels and each document can be …
words in held-out test documents, … from a set of pre-defined K labels and each document can be …
Finding structure in noisy text: topic classification and unsupervised clustering
… articles consisting of thousands of topic labels. Unlike most … -set, supervised classification
with a pre-defined set of topics, … typically assigns multiple topics to a document, a document …
with a pre-defined set of topics, … typically assigns multiple topics to a document, a document …
Unsupervised exemplar-based learning for improved document image classification
… approach trains a neural network model on an auxiliary task in which every training
example is associated with a different label (… A set of randomly-chosen combination of pre-defined …
example is associated with a different label (… A set of randomly-chosen combination of pre-defined …
ANNOTATE: orgANizing uNstructured cOntenTs viA Topic labEls
… The usage of manually-assigned tags for this purpose … classification, or are unsupervised
and rely on (undirected) … that either does not have a pre-defined data model or is not pre-…
and rely on (undirected) … that either does not have a pre-defined data model or is not pre-…