Papers Dynamic Topic Modeling
“Dynamic Topic Modeling” 태그가 달린 논문 20편 · 필터 해제
How Large Language Models Are Changing MOOC Essay Answers: A Comparison of Pre- and Post-LLM Responses
The release of ChatGPT in late 2022 caused a flurry of activity and concern in the academic and educational communities. Some see the tool's ability to generate human-like text that passes at least cursory inspections fo…
Dynamic Topic ModelingEthicsInformation RetrievalVisualizing Temporal Topic Embeddings with a Compass
Dynamic topic modeling is useful at discovering the development and change in latent topics over time. However, present methodology relies on algorithms that separate document and word representations. This prevents the …
DiversityDynamic Topic ModelingWord EmbeddingsHistoria Magistra Vitae: Dynamic Topic Modeling of Roman Literature using Neural Embeddings
Dynamic topic models have been proposed as a tool for historical analysis, but traditional approaches have had limited usefulness, being difficult to configure, interpret, and evaluate. In this work, we experiment with a…
Dynamic Topic ModelingTopic ModelsExploring Public Attention in the Circular Economy through Topic Modelling with Twin Hyperparameter Optimisation
To advance the circular economy (CE), it is crucial to gain insights into the evolution of public attention, cognitive pathways of the masses concerning circular products, and to identify primary concerns. To achieve thi…
Dynamic Topic ModelingHyperparameter OptimizationTopic ModelsWord EmbeddingsCFTM: Continuous time fractional topic model
In this paper, we propose the Continuous Time Fractional Topic Model (cFTM), a new method for dynamic topic modeling. This approach incorporates fractional Brownian motion~(fBm) to effectively identify positive or negati…
ArticlesDynamic Topic Modelingmodelparameter estimation+1ATEM: A Topic Evolution Model for the Detection of Emerging Topics in Scientific Archives
This paper presents ATEM, a novel framework for studying topic evolution in scientific archives. ATEM is based on dynamic topic modeling and dynamic graph embedding techniques that explore the dynamics of content and cit…
ArticlesDynamic graph embeddingDynamic Topic ModelingGraph EmbeddingANTM: An Aligned Neural Topic Model for Exploring Evolving Topics
This paper presents an algorithmic family of dynamic topic models called Aligned Neural Topic Models (ANTM), which combine novel data mining algorithms to provide a modular framework for discovering evolving topics. ANTM…
DiversityDynamic Topic ModelingTopic ModelsJointly Dynamic Topic Model for Recognition of Lead-lag Relationship in Two Text Corpora
Topic evolution modeling has received significant attentions in recent decades. Although various topic evolution models have been proposed, most studies focus on the single document corpus. However in practice, we can ea…
Dynamic Topic ModelingRecurrent Coupled Topic Modeling over Sequential Documents
The abundant sequential documents such as online archival, social media and news feeds are streamingly updated, where each chunk of documents is incorporated with smoothly evolving yet dependent topics. Such digital text…
Data AugmentationDynamic Topic ModelingAdapting CRISP-DM for Idea Mining: A Data Mining Process for Generating Ideas Using a Textual Dataset
Data mining project managers can benefit from using standard data mining process models. The benefits of using standard process models for data mining, such as the de facto and the most popular, Cross-Industry-Standard-P…
ArticlesBIG-bench Machine LearningDynamic Topic ModelingTransfer LearningOn Large-Scale Dynamic Topic Modeling with Nonnegative CP Tensor Decomposition
There is currently an unprecedented demand for large-scale temporal data analysis due to the explosive growth of data. Dynamic topic modeling has been widely used in social and data sciences with the goal of learning lat…
Dynamic Topic ModelingTensor DecompositionMixed Membership Recurrent Neural Networks
Models for sequential data such as the recurrent neural network (RNN) often implicitly model a sequence as having a fixed time interval between observations and do not account for group-level effects when multiple sequen…
Dynamic Topic ModelingDeep Temporal-Recurrent-Replicated-Softmax for Topical Trends over Time
Dynamic topic modeling facilitates the identification of topical trends over time in temporal collections of unstructured documents. We introduce a novel unsupervised neural dynamic topic model named as Recurrent Neural …
ArticlesDynamic Topic ModelingTopic ModelsLearning Methods for Dynamic Topic Modeling in Automated Behaviour Analysis
Semi-supervised and unsupervised systems provide operators with invaluable support and can tremendously reduce the operators load. In the light of the necessity to process large volumes of video data and provide autonomo…
Dynamic Topic ModelingScalable Dynamic Topic Modeling with Clustered Latent Dirichlet Allocation (CLDA)
Topic modeling, a method for extracting the underlying themes from a collection of documents, is an increasingly important component of the design of intelligent systems enabling the sense-making of highly dynamic and di…
ClusteringDynamic Topic ModelingExploring the Political Agenda of the European Parliament Using a Dynamic Topic Modeling Approach
This study analyzes the political agenda of the European Parliament (EP) plenary, how it has evolved over time, and the manner in which Members of the European Parliament (MEPs) have reacted to external and internal stim…
Dynamic Topic ModelingBayesian Analysis of Dynamic Linear Topic Models
In dynamic topic modeling, the proportional contribution of a topic to a document depends on the temporal dynamics of that topic's overall prevalence in the corpus. We extend the Dynamic Topic Model of Blei and Lafferty …
Data AugmentationDynamic Topic ModelingTopic ModelsComplex Politics: A Quantitative Semantic and Topological Analysis of UK House of Commons Debates
This study is a first, exploratory attempt to use quantitative semantics techniques and topological analysis to analyze systemic patterns arising in a complex political system. In particular, we use a rich data set cover…
Dynamic Topic ModelingTopological Data AnalysisUnveiling the Political Agenda of the European Parliament Plenary: A Topical Analysis
This study analyzes political interactions in the European Parliament (EP) by considering how the political agenda of the plenary sessions has evolved over time and the manner in which Members of the European Parliament …
Dynamic Topic ModelingVisualization of Clandestine Labs from Seizure Reports: Thematic Mapping and Data Mining Research Directions
The problem of spatiotemporal event visualization based on reports entails subtasks ranging from named entity recognition to relationship extraction and mapping of events. We present an approach to event extraction that …
Dynamic Topic ModelingEvent ExtractionInformation Retrievalnamed-entity-recognition+4