Search results for "topic model"

showing 3 items of 23 documents

A Survey of Multi-Label Topic Models

2019

Every day, an enormous amount of text data is produced. Sources of text data include news, social media, emails, text messages, medical reports, scientific publications and fiction. To keep track of this data, there are categories, key words, tags or labels that are assigned to each text. Automatically predicting such labels is the task of multi-label text classification. Often however, we are interested in more than just the pure classification: rather, we would like to understand which parts of a text belong to the label, which words are important for the label or which labels occur together. Because of this, topic models may be used for multi-label classification as an interpretable mode…

Topic modelInformation retrievalComputer scienceGeography Planning and DevelopmentFlexibility (personality)02 engineering and technologyTask (project management)ComputingMethodologies_PATTERNRECOGNITION020204 information systems0202 electrical engineering electronic engineering information engineeringKey (cryptography)General Earth and Planetary Sciences020201 artificial intelligence & image processingSocial mediaWater Science and TechnologyACM SIGKDD Explorations Newsletter
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Statistically Validated Networks for evaluating coherence in topic models

2022

Probabilistic topic models have become one of the most widespread machine learning technique for textual analysis purpose. In this framework, Latent Dirichlet Allocation (LDA) gained more and more popularity as a text modelling technique. The idea is that documents are represented as random mixtures over latent topics, where a distribution over words characterizes each topic. Unfortunately, topic models do not guarantee the interpretability of their outputs. The topics learned from the model may be characterized by a set of irrelevant or unchained words, being useless for the interpretation. In the framework of topic quality evaluation, the pairwise semantic cohesion among the top-N most pr…

Settore SECS-S/06 -Metodi Mat. dell'Economia e d. Scienze Attuariali e Finanz.Text Mining Probabilistic Topic Models Topic coherence Statistically Validated NetworksSettore SECS-S/01 - Statistica
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Using Topic Modeling Methods for Short-Text Data: A Comparative Analysis

2020

With the growth of online social network platforms and applications, large amounts of textual user-generated content are created daily in the form of comments, reviews, and short-text messages. As a result, users often find it challenging to discover useful information or more on the topic being discussed from such content. Machine learning and natural language processing algorithms are used to analyze the massive amount of textual social media data available online, including topic modeling techniques that have gained popularity in recent years. This paper investigates the topic modeling subject and its common application areas, methods, and tools. Also, we examine and compare five frequen…

Topic modelshort textInformation retrievalSocial networkbusiness.industryLatent semantic analysisComputer scienceRandom projectiontopic modelingUser-generated contentSubject (documents)Context (language use)Latent Dirichlet allocationlcsh:QA75.5-76.95symbols.namesakeArtificial Intelligenceonline social networkssymbolsMethodslcsh:Electronic computers. Computer sciencenatural language processingbusinessuser-generated contentFrontiers in Artificial Intelligence
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