Are school-of-thought words characterizable?

Xiaorui Jiang, Xiaoping Sun, Hai Zhuge*

*Corresponding author for this work

Research output: Chapter in Book/Published conference outputConference publication


School of thought analysis is an important yet not-well-elaborated scientific knowledge discovery task. This paper makes the first attempt at this problem. We focus on one aspect of the problem: do characteristic school-of-thought words exist and whether they are characterizable? To answer these questions, we propose a probabilistic generative School-Of-Thought (SOT) model to simulate the scientific authoring process based on several assumptions. SOT defines a school of thought as a distribution of topics and assumes that authors determine the school of thought for each sentence before choosing words to deliver scientific ideas. SOT distinguishes between two types of school-of-thought words for either the general background of a school of thought or the original ideas each paper contributes to its school of thought. Narrative and quantitative experiments show positive and promising results to the questions raised above

Original languageEnglish
Title of host publicationProceedings of the 51st Annual Meeting of the Association for Computational Linguistics
PublisherAssociation for Computational Linguistics
Number of pages7
ISBN (Print)978-1-937284-51-0
Publication statusPublished - 2013
Event51st annual meeting of the Association for Computational Linguistics - Sofia, Bulgaria
Duration: 4 Aug 20139 Aug 2013


Meeting51st annual meeting of the Association for Computational Linguistics
Abbreviated titleACL 2013


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