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Läsbarhetsalgoritmer: En utvärdering av möjligheten att bygga ut LIX-algoritmen
KTH, School of Computer Science and Communication (CSC).
KTH, School of Computer Science and Communication (CSC).
2014 (Swedish)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [sv]

Läsbarhet handlar om hur begriplig en text är och är ett område som har studerats under väldigt många år. I denna studie utvärderas möjligheten att bygga ut den existerande läsbarhetsalgoritmen LIX med syftet att konstruera en algoritm som gör en mer exakt bedömning. I studien utvecklas en algoritm baserat på LIX och tidigare forskning inom läsbarhet, även sambandet mellan läsbarhetsnivå och ordklassfördelning undersöks. Under studien visade det sig att det finns ett samband mellan en texts läsbarhetsnivå och andelen verb och substantiv. Algoritmen byggdes ut med två parametrar; andelen vanliga ord samt skillnaden mellan andelen verb och substantiv. Resultatet visade att den nya algoritmen ger ett åtminstone lika bra resultat som LIX-algoritmen. Det var dock inte möjligt att dra några slutsatser om dess exakthet i jämförelse med LIX-algoritmen då resultatet av testerna som involverade mänsklig bedömning var undermåligt. Vidare diskuteras då hurman kan få pålitliga resultat från läsbarhetstester som baseras på mänsklig bedömning.

Abstract [en]

Readability is about how comprehensible a text is and it is a field which has been studied for many years. In this study the possibility of expanding the readability algorithm LIX, with the purpose of constructing an algorithmwhich is more exact, is evaluated. In the study an algorithm is developed based on LIX and earlier research within readability. The relation between readability level and the parts of speech distribution is also evaluated. During the study it was shown that there is a relation between the readability of a text and the proportion of verb and noun. The algorithm was expanded with two parameters; the number of common words and the difference between the proportion of verbs and nouns. The result showed that the new algorithm gave a result that was at least equally good to that of LIX. It was not possible to draw any conclusion to the new algorithm’s accuracy in comparison to LIX due to the substandard quality of the test involving human evaluation. Further it is discussed how more reliable results can beobtained from readability tests based on human evaluation.

Place, publisher, year, edition, pages
2014.
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-157675OAI: oai:DiVA.org:kth-157675DiVA: diva2:771043
Examiners
Available from: 2014-12-12 Created: 2014-12-12 Last updated: 2014-12-12Bibliographically approved

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