NDLI: Estimating content concreteness for finding comprehensible documents

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Estimating content concreteness for finding comprehensible documents

Content Provider	ACM Digital Library
Author	Kato, Makoto P. Tanaka, Katsumi Jatowt, Adam Tanaka, Shinya
Abstract	Document comprehensibility is one of key factors determining document quality and, in result, user's satisfaction. Relevant web pages are of little utility if they are incomprehensible or impose too much cognitive burden on readers. Traditional measures of text difficulty focus often on syntactic factors of text such as sentence length, word length, syllable count, or they utilize fixed list of common terms. However, document comprehensibility depends on many factors, of which concreteness and the ease of concept visualization are crucial ones. In this paper, we first propose a method for predicting the concreteness of terms using SVM regression. We then extend it to calculating document concreteness level. The experimental results indicate satisfactory accuracy in estimating both term and document concreteness as well as demonstrate positive correlation between the document concreteness and comprehensibility. Our ultimate goal is to enable comprehension-driven search, which will return both relevant and comprehensible results.
Starting Page	475
Ending Page	484
Page Count	10
File Format	PDF
ISBN	9781450318693
DOI	10.1145/2433396.2433455
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-02-04
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Concreteness Comprehensibility Readability Abstractness Information retrieval
Content Type	Text
Resource Type	Article

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