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--- nlp:topic_detection [2021/05/07 20:02] – created jmflanig
+++ nlp:topic_detection [2023/06/15 07:36] (current) – external edit 127.0.0.1
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 ====== Topic Detection ======
+===== Within a Discourse =====
   * [[https://www.aclweb.org/anthology/N03-3001.pdf|2003 - Semantic Language Models for Topic Detection and Tracking]]
-  * [[https://www.aclweb.org/anthology/Q19-1011.pdf|2019 - SECTOR: A Neural Model for Coherent Topic Segmentation and Classification]]
+  * [[https://www.aclweb.org/anthology/W15-4615.pdf|Kim et al 2015 - Towards Improving Dialogue Topic Tracking Performances with Wikification of Concept Mentions]]
+  * [[https://www.aclweb.org/anthology/I11-1066.pdf|Zhang et al 2016 - Thread Cleaning and Merging for Microblog Topic Detection]]
+  * [[https://www.aclweb.org/anthology/Q19-1011.pdf|2019 - SECTOR: A Neural Model for Coherent Topic Segmentation and Classification]] Says "topic modeling (Blei et al., 2003) and TDT (Jin et al., 1999) focus on representing and extracting the semantic topical content of text. Text segmentation (Beeferman et al.1999) is used to split documents into smaller coherent chunks. Finally, text classification (Joachims 1998)  is  often  applied  to  detect  topics  on  text chunks. Our method unifies those strongly inter-woven tasks and is the first to evaluate the combined  topic  segmentation  and  classification  task using a corresponding data set with long structured documents."
+===== Change Over Time Across Documents =====
+  * [[https://www.aclweb.org/anthology/Y14-1011.pdf|Chang et al 2014 - Semantic Frame-based Statistical Approach for Topic Detection]]
+  * [[https://www.aclweb.org/anthology/W16-5702.pdf|Bruggermann et al 2016 - Storyline Detection and Tracking Using Dynamic Latent Dirichlet Allocation]]
+===== Related Pages =====
+  * [[Discourse Analysis#Discourse Coherence]]