Relevance Feedback pada Temu Kembali Informasi Menggunakan Algoritma Genetika

Main Authors: Hariyono, Muhammad Erwin Ashari, Mandala, Rila
Format: Article info application/pdf eJournal
Bahasa: eng
Terbitan: Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia , 2009
Online Access: http://journal.uii.ac.id/index.php/Snati/article/view/1816
http://journal.uii.ac.id/index.php/Snati/article/view/1816/1595
Daftar Isi:
  • This paper proposes a method to improve the performance of information retrievalsystems by expanding queries using genetic algorithm. The expansion terms are taken usingrelevance feedback from user judgment process in response of document retrieved.Experiment using international standard text collections (CISI, CACM and INSPECcollection) which consist more than one thousand document each collection proved that thismethod could improve the information retrieval. This method has been developed and testedusing Non Interpolated Average Precision (NAP) as an evaluation formula. The results of thetest are discussed, and some directions for further works are pointed out.Keywords: Query expansion, information retrieval, term weighting, genetic algorithm,document retrieval