Celal Bayar University

About: Celal Bayar University is a education organization based out in Magnesia ad Sipylum, Turkey. It is known for research contribution in the topics: Population & Heat transfer. The organization has 2960 authors who have published 6024 publications receiving 100646 citations.

Exploring Performance of Instance Selection Methods in Text Sentiment Classification

Abstract: Sentiment analysis is the process of extracting subjective information in source materials. Sentiment analysis is a subfield of web and text mining. One major problem encountered in these areas is overwhelming amount of data available. Hence, instance selection and feature selection become two essential tasks for achieving scalability in machine learning based sentiment classification. Instance selection is a data reduction technique which aims to eliminate redundant, noisy data from the training dataset so that training time can be reduced, scalability and generalization ability can be enhanced. This paper examines the predictive performance of fifteen benchmark instance selection methods for text classification domain. The instance selection methods are evaluated by decision tree classifier (C4.5 algorithm) and radial basis function networks in terms of classification accuracy and data reduction rates. The experimental results indicate that the highest classification accuracies on C4.5 algorithm are generally obtained by model class selection method, while the highest classification accuracies on radial basis function networks are obtained by nearest centroid neighbor edition.

Pandoraea oxalativorans sp. nov., Pandoraea faecigallinarum sp. nov. and Pandoraea vervacti sp. nov., isolated from oxalate-enriched culture.

Abstract: Five isolates, designated TA2, TA4, TA25(T), KOx(T) and NS15(T) were isolated in previous studies by enrichment in mineral medium with potassium oxalate as the sole carbon source and were characterized using a polyphasic approach. The isolates were Gram-reaction-negative, aerobic, non-spore-forming rods. Phylogenetic analyses based on 16S rRNA and DNA gyrase B subunit (gyrB) gene sequences confirmed that the isolates belonged to the genus Pandoraea and were most closely related to Pandoraea sputorum and Pandoraea pnomenusa (97.2-99.70/0 16S rRNA gene sequence similarity). The isolates could be differentiated from their closest relatives on the basis of several phenotypic characteristics. The major cellular fatty acid profiles of the isolates comprised C(16:0), C(18:1)omega 7c, C(17:0) cyclo and summed feature 3 (C(16:1)omega 7c and/or iso-C(15:0) 2-OH). On the basis of DNA DNA hybridization studies and phylogenetic analyses, the isolates represent three novel species within the genus Pandoraea, for which the names Pandoraea oxalativorans sp. nov. (TA25(T) =NBRC 106091(T) =CCM 7677(T) =DSM 23570(T)), Pandoraea faecigallinarum sp. nov. (KOx(T) =NBRC 106092(T) =CCM 2766(T) =DSM 23572(T)) and Pandoraea vervacti sp. nov. (NS15(T) =NBRC 106088(T) =CCM 7667(T) =DSM 235711) are proposed.