Please use this identifier to cite or link to this item: https://doi.org/10.1145/1816123.1816155
Title: Domain-specific iterative readability computation
Authors: Zhao, J. 
Kan, M.-Y. 
Keywords: Domain-specific information retrieval
Graph-based algorithm
Iterative computation
Readability measure
Issue Date: 2010
Source: Zhao, J.,Kan, M.-Y. (2010). Domain-specific iterative readability computation. Proceedings of the ACM International Conference on Digital Libraries : 205-214. ScholarBank@NUS Repository. https://doi.org/10.1145/1816123.1816155
Abstract: We present a new algorithm to measure domain-specific readability. It iteratively computes the readability of domain-specific resources based on the difficulty of domain-specific concepts and vice versa, in a style reminiscent of other bipartite graph algorithms such as Hyperlink-Induced Topic Search (HITS) and the Stochastic Approach for Link-Structure Analysis (SALSA). While simple, our algorithm outperforms standard heuristic measures and remains competitive among supervised-learning approaches. Moreover, it is less domain-dependent and portable across domains as it does not rely on an annotated corpus or expensive expert knowledge that supervised or domain-specific methods require. © 2010 ACM.
Source Title: Proceedings of the ACM International Conference on Digital Libraries
URI: http://scholarbank.nus.edu.sg/handle/10635/40292
ISBN: 9781450300858
DOI: 10.1145/1816123.1816155
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