Cross Validation Of Neural Network Applications For Automatic New Topic Identification

There are recent studies in the literature on automatic topic-shift identification in Web search engine user sessions; however most of this work applied their topic-shift identification algorithms on data logs from a single search engine. The purpose of this study is to provide the cross-validation of an artificial neural network application to automatically identify topic changes in a web search engine user session by using data logs of different search engines for training and testing the neural network. Sample data logs from the Norwegian search engine FAST (currently owned by Overture) and Excite are used in this study. Findings of this study suggest that it could be possible to identify topic shifts and continuations successfully on a particular search engine user session using neural networks that are trained on a different search engine data log

Investigating the Performance of Automatic New Topic Identification Across Multiple Datasets

Recent studies on automatic new topic identification in Web search engine user sessions demonstrated that neural networks are successful in automatic new topic identification. However most of this work applied their new topic identification algorithms on data logs from a single search engine. In this study, we investigate whether the application of neural networks for automatic new topic identification are more successful on some search engines than others. Sample data logs from the Norwegian search engine FAST (currently owned by Overture) and Excite are used in this study. Findings of this study suggest that query logs with more topic shifts tend to provide more successful results on shift-based performance measures, whereas logs with more topic continuations tend to provide better results on continuation-based performance measures

Orta Öğretim Öğrencilerinin Orijinal Düşünmeye İlişkin Görüşlerinin Çeşitli Değişkenlere Göre İncelenmesi: Kars Örneği

The main purpose of this study was to examine the secondary 5th-, 6th-, and 7th-grade students' views on original thinking in the dimensions of flexibility, originality, elaboration, and fluency. The study group of this descriptive study that was handled in the form of a survey model consisted of 540 students attending fifth, sixth and seventh grades, in the central district of Kars, during the 2012-2013 school-year, second semester. After eliminating the missing data, the study group consisted totally of 314 students. Original thinking questionnaire was used to collect qualitative data. As a result of the original thinking research, secondary school students received the highest score from the sub-dimension of fluency. However, depending on these findings, it has been found that, according to grade level, fifth-grade students, and according to gender variable, female students can think more originallyBu araştırmanın temel amacı, ortaokul 5,6 ve 7. sınıf öğrencilerinin orijinal düşünmenin esneklik, özgünlük, ayrıntılama ve akıcılık boyutlarına ilişkin görüşlerini incelemektir. Tarama modelinde yürütülmüş betimsel araştırmanın çalışma grubunu, 2012-2013 öğretim yılının 2. döneminde, Kars ili merkez ilçede bulunan okulların beşinci, altıncı ve yedinci sınıflarına devam eden toplam 540 öğrenci oluşturmuştur. Kayıp veriler elendikten sonra, çalışma grubu toplam 314 öğrenciden oluşmuştur. Araştırmada veri toplama aracı olarak orijinal düşünme anketi kullanılmıştır. Araştırmanın sonucunda ortaokul öğrencilerinin orijinal düşünme anketinde en yüksek puanı akıcılık alt boyutunda aldıkları görülmüştür. Yine elde edilen bulgular ışığında, sınıf düzeyine göre beşinci sınıf öğrencilerinin ve cinsiyet değişkenine göre kız öğrencilerin daha orijinal düşünebildikleri sonuçlarına ulaşılmıştır