Are School-of-thought Words Characterizable?

Xiaorui Jiang, Xiaoping Sun, Hai Zhuge

Research output: Chapter in Book/Report/Conference proceedingConference proceedingpeer-review

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Abstract

School of thought analysis is an important yet not-well-elaborated scientific knowledge dis-covery 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 characteriza-ble? To answer these questions, we propose a probabilistic generative School-Of-Thought (SOT) model to simulate the scientific author-ing 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 back-ground of a school of thought or the original ideas each paper contributes to its school of thought. Narrative and quantitative experi-ments 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 (Volume 2: Short Papers)
PublisherACL (Association for Computational Linguistics)
Pages822-828
Number of pages7
Volume2
Publication statusPublished - Aug 2013
Externally publishedYes
Event51st Annual Meeting of the Association for Computational Linguistics - Sofia, Bulgaria
Duration: 4 Aug 20139 Aug 2013
Conference number: 51

Conference

Conference51st Annual Meeting of the Association for Computational Linguistics
CountryBulgaria
CitySofia
Period4/08/139/08/13

Bibliographical note

Licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 International License. Permission is granted to make copies for the purposes of teaching and research.

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