Context-Aware Stemming Algorithm for Semantically Related Root Words

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dc.contributor.authorAgbele, Kehinde K.
dc.contributor.authorAdesina, A. O.
dc.contributor.authorAzeez, N. A.
dc.contributor.authorAbidoye, A. P.
dc.date.accessioned2019-06-27T07:52:22Z
dc.date.available2019-06-27T07:52:22Z
dc.date.issued2012-06
dc.description.abstractThere is a growing interest in the use of context-awareness as a technique for developing pervasive computing applications that are flexible and adaptable for users. In this context, however, information retrieval (IR) is often defined in terms of location and delivery of documents to a user to satisfy their information need. In most cases, morphological variants of words have similar semantic interpretations and can be considered as equivalent for the purpose of IR applications. Consequently, document indexing will also be more meaningful if semantically related root words are used instead of stems. The popular Porter’s stemmer was studied with the aim to produce intelligible stems. In this paper, we propose Context-Aware Stemming (CAS) algorithm, which is a modified version of the extensively used Porter’s stemmer. Considering only generated meaningful stemming words as the stemmer output, the results show that the modified algorithm significantly reduces the error rate of Porter’s algorithm from 76.7% to 6.7% without compromising the efficacy of Porter’s algorithm.en_US
dc.identifier.citationAgbele, K. K., Adesina, A. O., Azeez, N. A., & Abidoye, A. P. (2012). Context-Aware Stemming algorithm for semantically related root words.en_US
dc.identifier.issnISSN 2006-1781
dc.identifier.urihttp://repository.elizadeuniversity.edu.ng/handle/20.500.12398/199
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectContext-awarenessen_US
dc.subjectInformation retrievalen_US
dc.subjectStemmingen_US
dc.subjectPrecisionen_US
dc.subjectRecalen_US
dc.titleContext-Aware Stemming Algorithm for Semantically Related Root Wordsen_US
dc.typeArticleen_US
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