Topic segmentation with an ordering-based topic model

Lan Du, John K Pate, Mark Johnson

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8 Citations (Scopus)


Documents from the same domain usually discuss similar topics in a similar order. However, the number of topics and the exact topics discussed in each individual document can vary. In this paper we present a simple topic model that uses generalised Mallows models and incomplete topic orderings to incorporate this ordering regularity into the probabilistic generative process of the new model. We show how to reparame-terise the new model so that a point-wise sampling algorithm from the Bayesian word segmentation literature can be used for inference. This algorithm jointly samples not only the topic orders and the topic assignments but also topic segmentations of documents. Experimental results show that our model performs significantly better than the other ordering-based topic models on nearly all the corpora that we used, and competitively with other state-of-the-art topic segmentation models on corpora that have a strong ordering regularity.
Original languageEnglish
Title of host publicationProceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence
Subtitle of host publicationJanuary 25 – 30, 2015 Hyatt Regency Austin, Austin, Texas, USA
EditorsBlai Bonet, Sven Koenig
Place of PublicationPalo Alto California USA
PublisherAssociation for the Advancement of Artificial Intelligence (AAAI)
Number of pages7
ISBN (Print)9781577357018
Publication statusPublished - 2015
Externally publishedYes
EventAAAI Conference on Artificial Intelligence 2015 - Hyatt Regency, Austin, United States of America
Duration: 25 Jan 201530 Jan 2015
Conference number: 29th


ConferenceAAAI Conference on Artificial Intelligence 2015
Abbreviated titleAAAI 2015
CountryUnited States of America
OtherCo-located with the 27th Innovative Applications of Artificial Intelligence Conference. Papers at the AAAI 2015 conference will be related here. Any papers presented at the IAAI 2015 part of the conference will be related to that event. The two conferences should have a "relation" to each other put in place to recognise that the conferences were combined into one proceedings.
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