Clustering of tree-structured data objects



Performance tests of a novel electroencephalographic data-acquisition system
Usakli, Ali Bulent; Gençer, Nevzat Güneri (2007-02-16)
The aim of the this study is to present some performance tests of a novel 256-channel electroencephalographic data-acquisition system. The common mode rejection ratio of the system was measured as 102 dB for signals in the electroencephalography frequency range and 154 dB for de signals. System electrical noise (referred-to-input) is 1.76 mu V (rms) (0.21 mu V/root Hz for 70-Hz bandwidth). The cross-talk rejection was found to be at 58 dB. The dynamic range of the system was found 108 dB. The performance te...
Context aware friend recommendation for location based social networks using random walk
Bağcı, Hakan; Karagöz, Pınar (null; 2016-04-10)
The location-based social networks (LBSN) facilitate users to check-in their current location and share it with other users. The accumulated check-in data can be employed for the benefit of users by providing personalized recommendations. In this paper, we propose a random walk based context-aware friend recommendation algorithm (RWCFR). RWCFR considers the current context (i.e. current social relations, personal preferences and current location) of the user to provide personalized recommendations. Our LBSN...
Learning-based methods for multi-modal and multi-spectral data
Özkan, Savaş; Akar, Gözde; Department of Electrical and Electronics Engineering (2020-10-15)
Data-driven solutions have become essential parts of our daily lives. These solutions generally consume a large amount of supervised data. Additionally, a large-body of learnable parameters must be trained to be able to reach the level of human knowledge accurately. However, these dependencies can be overcome by making full use of domain-specific features via specialized learning structures. This thesis addresses unsupervised and multimodal data by utilizing different sensor types and application doma...
Hybrid learning algorithm for intelligent short-term load forecasting
Kumluca Topallı, Ayça; Erkmen, İsmet; Department of Electrical and Electronics Engineering (2003)
Short-term load forecasting (STLF) is an important part of the power generation process. For years, it has been achieved by traditional approaches stochastic like time series; but, new methods based on artificial intelligence emerged recently in literature and started to replace the old ones in the industry. In order to follow the latest developments and to have a modern system, it is aimed to make a research on STLF in Turkey, by neural networks. For this purpose, a method is proposed to forecast Turkey̕s ...
Integration of fuzzy object-oriented multimedia database components
Demir, Utku; Yazıcı, Adnan; Department of Computer Engineering (2010)
Improvements in technology have increased the amount of human interactive systems that support visual and audial operations. Besides many others, especially the recent entertainment industry has been built on the digital world and processing large collections of multimedia materials. Having huge amount multimedia data revealed the need for efficient and effective ways of modeling, storing, addressing, and retrieving such huge data, mostly, the semantic contents in it. Although there are some database manage...
Citation Formats
D. Dinler, M. K. Tural, and N. E. Özdemirel, “Clustering of tree-structured data objects,” presented at the 10th International Statistics Congress (2017), Ankara, Turkey, 2017, Accessed: 00, 2021. [Online]. Available: