Domain-specific iterative readability computation

We present a new algorithm to measure domain-specific readability. It iteratively computes the readability of domainspecific 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 domaindependent and portable across domains as it does not rely on an annotated corpus or expensive expert knowledge that supervised or domain-specific methods require. Categories and Subject Descriptors H.3.1 [Information Storage and Retrieval]: Content Analysis and Indexing; H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval; J.2 [Computer Applications]: Physical Sciences and Engineering General Terms Algorithm, Measurement Keywords Readability...

• Type: Conference
• Year: 2010
• Where: JCDL
• Authors: Jin Zhao, Min-Yen Kan
• Keywords: Algorithm, Domain-Specific Information Retrieval, Domain-specific Readability, Education, JCDL 2010