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2009 Ninth International Conference on Intelligent Systems Design and Applications, 2009
An algorithm for the automatic labeling of topics accordingly to a hierarchy is presented. Its main ingredients are a set of similarity measures and a set of topic labeling rules. The labeling rules are specifically designed to find the most agreed labels between the given topic and the hierarchy.
STELLA, FABIO ANTONIO +3 more
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An algorithm for the automatic labeling of topics accordingly to a hierarchy is presented. Its main ingredients are a set of similarity measures and a set of topic labeling rules. The labeling rules are specifically designed to find the most agreed labels between the given topic and the hierarchy.
STELLA, FABIO ANTONIO +3 more
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Document classification by topic labeling
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval, 2013In this paper, we propose Latent Dirichlet Allocation (LDA) [1] based document classification algorithm which does not require any labeled dataset. In our algorithm, we construct a topic model using LDA, assign one topic to one of the class labels, aggregate all the same class label topics into a single topic using the aggregation property of the ...
Swapnil Hingmire +3 more
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2013 2nd IAPR Asian Conference on Pattern Recognition, 2013
We propose a Label-Related/Unrelated Topic Switching Model (LRU-TSM) based on Latent Dirichlet Allocation (LDA) for modeling a labeled corpus. In this model, each word is allocated to a label-related topic or a label-unrelated topic. Label-related topics utilize label information, and label-unrelated topics utilize the framework of Bayesian ...
Yasutoshi Ida +2 more
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We propose a Label-Related/Unrelated Topic Switching Model (LRU-TSM) based on Latent Dirichlet Allocation (LDA) for modeling a labeled corpus. In this model, each word is allocated to a label-related topic or a label-unrelated topic. Label-related topics utilize label information, and label-unrelated topics utilize the framework of Bayesian ...
Yasutoshi Ida +2 more
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Automatically Labelled Software Topic Model
International Journal of Open Source Software and Processes, 2020Public software repositories (SR) maintain a massive amount of valuable data offering opportunities to support software engineering (SE) tasks. Researchers have applied information retrieval techniques in mining software repositories. Topic models are one of these techniques.
Youcef Bouziane +2 more
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Automatic labeling hierarchical topics
Proceedings of the 21st ACM international conference on Information and knowledge management, 2012Recently, statistical topic modeling has been widely applied in text mining and knowledge management due to its powerful ability. A topic, as a probability distribution over words, is usually difficult to be understood. A common, major challenge in applying such topic models to other knowledge management problem is to accurately interpret the meaning ...
Xianling Mao +5 more
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Multi-label feature selection based on the division of label topics
Information Sciences, 2021zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ping Zhang 0025 +3 more
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A Label Distribution Topic Model for Multi-label Classification
Proceedings of the 2019 4th International Conference on Intelligent Information Processing, 2019At present, multi-label supervised topic model is a kind of effective multi-label classification model applied to various domain. However, due to the limitation of traditional label-topic correspondence in existing multi-label supervised topic model, there are still some aspects that need to be improved.
Lin Liu, Lin Tang
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Automatic Labeling for Hierarchical Topics with NETL
2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2020Hierarchical topic model is the method used in considering topics with hierarchical relationships. Neural embedding topic labelling (NETL) is a method utilized to label topics with neural embedding, even though it labels topics without topic relationships. The labels of hierarchical topics should have hierarchical relationship with other labels.
Rinto Kozono, Ryosuke Saga
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Off-label Uses of Topical Pimecrolimus
Journal of Cutaneous Medicine and Surgery, 2019Pimecrolimus is a topical calcineurin inhibitor currently approved for second-line use in the management of mild-to-moderate atopic dermatitis in patients age 2 years and older. Given the safety profile and nonsteroidal mechanism of pimecrolimus, there has been significant interest in its use in the treatment of a variety of dermatological conditions ...
Matthew Ladda +3 more
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Multi-label Classification via Label-Topic Pairs
2018The task of learning from multi-label example is rather challenging because of the tremendous number of possible label sets. It has been well recognized that exploiting label relationships in a proper way can facilitate the learning process and boost the learning performance.
Gang Chen, Yue Peng, Chongjun Wang
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