A density-based method for adaptive LDA model selection

Cao, Juan; Xia, Tian; Li, Jintao; Zhang, Yongdong; Tang, Sheng

doi:10.1016/j.neucom.2008.06.011

Cited by 624 publications

(422 citation statements)

References 8 publications

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“…In the resulting scree plot, the log-likelihood will initially increase as a function of T, flattens at optimal models, and may decrease after that, indicating a large number of topics (Griffiths & Steyvers, 2004;Kosinski et al, 2016). Cao et al (2009) developed a density-based method for adaptive LDA model selection. They started from the observation that when K is too small (i.e., with only a few topics), the discrimination between the topics is low, once there are words that overlap across topics.…”

Section: Selecting the Number Of Topics: Cross-validation Analysesmentioning

confidence: 99%

“…The main feature of the approach of Cao et al (2009) is that it integrates a clustering process based on density, considering a topic as equivalent to a semantic cluster. The best model will have the largest possible intra-cluster similarity, which means that the cluster (i.e., the topic) includes coherent semantic content.…”

Section: Selecting the Number Of Topics: Cross-validation Analysesmentioning

confidence: 99%

“…The Seven-Topic Model (Table 4) was identified as an "optimal" model by the Cao et al (2009) method. To analyze the semantic content of this topic, we compared it with other seven-factor models Benet-Martinez & Waller, 1997;Church et al, 1998;Saucier, 2003) and with the Big Five (Goldberg & Rosolack, 1994).…”

Section: Seven-topic Modelmentioning

confidence: 99%

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The Personality Lexicon in Brazilian Portuguese: Studies with Natural Language

Peres¹

2018

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iv Procura da poesia (...) Chega mais perto e contempla as palavras.Cada uma tem mil faces secretas sob a face neutra e te pergunta, sem interesse pela resposta, pobre ou terrível, que lhe deres:Trouxeste a chave? (...) Carlos Drummond de Andrade in A Rosa do Povo (1945) From March 1979Tired of all who come with words, words but no language I went to the snow-covered island.The wild does not have words.The unwritten pages spread out on all sides! I come upon the tracks of roe deer in the snow.Language but no words. Tomas Tranströmer in The Wild Market Square (1983, trad. Robin Fulton) v DedicatoryThis dissertation is dedicated to Professor Jacob Laros and to Professor Luiz Pasquali, who advised me during my postgraduate studies with inspiring wisdom, not only embracing my projects, but also kindly respecting my ideas and decisions, and patiently guiding me through my doubts and after my stumbles. It is an honor to be an apprentice and a friend of such masters.vi Agradecimentos (Acknowledgements)Um doutoramento não é resultado apenas da dedicação individual do estudante. Nesse sentido, faço os seguintes agradecimentos. À Renata e ao Bartholomeu, pelo amor e companheirismo. Aos meus pais, que sempre se esforçaram para oferecer aos filhos e a outros familiares oportunidades para o desenvolvimento educacional e profissional. Aos meus irmãos, cunhados e ao restante da minha grande e querida família mineira. À Thaís, Dudu e Raphael, a quem espero inspirar em seguir a carreira acadêmica. Aos meus professores da Educação Básica, que me ensinaram a aprender e inspiraram minha predileção pela ciência, artes e filosofia. Gostaria de lembrar especialmente das professoras Laudiene, Eliana, Magda Table 3. The Six-Topic Model with the 10 most relevant terms of the topics, reliability and presumed correspondence with other psycholexical models ……………………………………………………………..……….… 127 Table 4. The Seven-Topic Model with the 10 most relevant terms of the topics, reliability and presumed correspondence with other psycholexical models ……………………………………………………….… 128 Table 5. The Fourteen-Topic Model with the 10 most relevant terms of the topics, reliability and presumed correspondence with other psycholexical models ………………………………………………………… 130 Table 6. The Fifteen-Topic Model with the 10 most relevant terms of the topics, reliability and presumed correspondence with other psycholexical models …………………………………………………………. 132 Table 7. User frequency or the number of users that used the term, overall term frequency in the corpus, inverse document frequency, mean, minimum, maximum, and range …………………………..… 147xii General AbstractThis dissertation consists of three studies concerning the lexical approach of research in the field of personality, with a focus on Brazilian culture and natural language. The first study is of a theoretical nature and explores some of the criticisms regarding the lexical approach to personality research with its origin in the psychological study of natural language and crosscultural psychology, as well as methodolo...

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Section: Selecting the Number Of Topics: Cross-validation Analysesmentioning

confidence: 99%

Section: Selecting the Number Of Topics: Cross-validation Analysesmentioning

confidence: 99%

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The Personality Lexicon in Brazilian Portuguese: Studies with Natural Language

Peres¹

2018

Preprint

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“…The LDA uses the parameters shown in Table 2. In addition, several methods for selecting the optimal number of topics have already been proposed [23,24,[31][32][33]. We used the method Cao et al proposed, which is considered to be the most appropriate method for this study [31].…”

Section: Experiments Resultsmentioning

confidence: 99%

“…There are various opinions on how to determine the optimal number of topics [23,24,[30][31][32]. For our purposes, the topic is determined by the topic probability θ of each document.…”

Section: Componentmentioning

confidence: 99%

Ensemble Modeling for Sustainable Technology Transfer

et al. 2018

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These days, technological advances are being made through technological conversion. Following this trend, companies need to adapt and secure their own sustainable technological strategies. Technology transfer is one such strategy. This method is especially effective in coping with recent technological developments. In addition, universities and research institutes are able to secure new research opportunities through technology transfer. The aim of our study is to provide a technology transfer prediction model for the sustainable growth of companies. In the proposed method, we first collected patent data from a Korean patent information service provider. Next, we used latent Dirichlet allocation, which is a topic modeling method used to identify the technical field of the collected patents. Quantitative indicators on the patent data were also extracted. Finally, we used the variables that we obtained to create a technology transfer prediction model using the AdaBoost algorithm. The model was found to have sufficient classification performance. It is expected that the proposed model will enable universities and research institutes to secure new technology development opportunities more efficiently. In addition, companies using this model can maintain sustainable growth in line, coping with the changing pace of society.

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Topic modeling of maintenance logs for linac failure modes and trends identification

Yun

Carlone

Liu

2021

J Applied Clin Med Phys

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Medical linear accelerators (linacs) can fail in a multitude of different manners due to complex structures. An unclear identification of failure modes occurring constantly is a major obstacle to maintenance arrangements, thereby may increasing downtime. This study aims to use natural language processing techniques to deal with the unformatted maintenance logs to identify the linac failure modes and trends over time. Materials and methods:The data used in our study are unformatted narrative maintenance logs recording linac conditions and repair actions. The latent Dirichlet allocation-based topic modeling method was used to identify topics and keywords regarding the failure modes. The temporal analysis method was applied to examine the variation of failure modes over 20 years. Results: Based on the output of the topic modeling, 28 topics and keywords with frequency ranking were generated automatically. The latent failure modes in topics were identified and classified into six main subsystems of linacs. Furthermore, by using the temporal analysis method, the trends of all failure modes over 20 years were illustrated. Half of the topics demonstrated variations with three different patterns, namely periodic, increasing, and decreasing. Conclusions:The results of our study validated the effectiveness of using the topic modeling method to automatically analyze narrative maintenance logs. With domain knowledge, failure modes of linacs can be identified and categorized quantitatively.

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A density-based method for adaptive LDA model selection

Cited by 624 publications

References 8 publications

The Personality Lexicon in Brazilian Portuguese: Studies with Natural Language

The Personality Lexicon in Brazilian Portuguese: Studies with Natural Language

Ensemble Modeling for Sustainable Technology Transfer

Topic modeling of maintenance logs for linac failure modes and trends identification

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