A Hybrid geo-activity recommendation system using advanced feature combination and semantic activity similarity

Download

index.pdf

Date

2013

Author

Sattari, Masoud

Metadata

Show full item record

Item Usage Stats

273
views

117
downloads

In this study, a new method for analyzing and representing the discriminative information, distributed in functional Magnetic Resonance Imaging (fMRI) data, is proposed. For this purpose, a local mesh with varying size is formed around each voxel, called the seed voxel. The relationships among each seed voxel and its neighbors are estimated using a linear regression equation by minimizing the expectation of the squared error. This squared error coming from linear regression is used to calculate various information theoretic criteria. Then, the optimal mesh size, which represents the connections among a voxel and its neighbors, is estimated by minimizing these information theoretic criteria with respect to mesh size. The optimal mesh size is used to represent the degree of connectivity such that if the optimal mesh size is small, then the voxel is assumed to be connected with a small number of neighbors. On the other hand, high optimal mesh size indicates that voxels are massively connected. The proposed method shows that the local mesh size with the highest discriminative power depends on the participants, samples in the experiment, and voxels. The results indicate that the local mesh model with optimal mesh size can successfully represent discriminative information.

Subject Keywords

Magnetic resonance imaging, Global system for mobile communications., Recommender systems (Information filtering)., Information filtering systems., Smartphones.

URI

http://etd.lib.metu.edu.tr/upload/12616497/index.pdf
https://hdl.handle.net/11511/23059

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

An Information theoretic representation of brain connectivity for cognitive state classification using functional magnetic resonance imaging Önal, Itır; Yarman Vural, Fatoş Tunay; Department of Computer Engineering (2013) In this study, a new method for analyzing and representing the discriminative information, distributed in functional Magnetic Resonance Imaging (fMRI) data, is proposed. For this purpose, a local mesh with varying size is formed around each voxel, called the seed voxel. The relationships among each seed voxel and its neighbors are estimated using a linear regression equation by minimizing the expectation of the squared error. This squared error coming from linear regression is used to calculate various info...
Representation of human brain by mesh networks Önal Ertuğrul, Itır; Yarman Vural, Fatoş Tunay; Department of Computer Engineering (2017) In this thesis, we propose novel representations to extract discriminative information in functional Magnetic Resonance Imaging (fMRI) data for cognitive state and gender classification. First, we model the local relationship among a set of fMRI time series within a neighborhood by considering temporal information obtained from all measurements in time series. The estimated local relationships, called Mesh Arc Descriptors (MADs), are employed to represent information in fMRI data. Second, we adapt encoding ...
A temporal neural network model for constructing connectionist expert system knowledge bases Alpaslan, Ferda Nur (Elsevier BV, 1996-04-01) This paper introduces a temporal feedforward neural network model that can be applied to a number of neural network application areas, including connectionist expert systems. The neural network model has a multi-layer structure, i.e. the number of layers is not limited. Also, the model has the flexibility of defining output nodes in any layer. This is especially important for connectionist expert system applications.
A Hypergraph based framework for representing aggregated user profiles, employing it for a recommender system and personalized search through a hypernetwork method Tarakçı, Hilal; Manguoğlu, Murat; Çiçekli, Fehime Nihan; Department of Computer Engineering (2017) In this thesis, we present a hypergraph based user modeling framework to aggregate partial profiles of the individual and obtain a complete, semantically enriched, multi-domain user model. We also show that the constructed user model can be used to support different personalization services including recommendation. We evaluated the user model against datasets consisting of user's social accounts including Facebook, Twitter, LinkedIn and Stack Overflow. The evaluation results confirmed that the proposed use...
A Parametric Estimation Approach to Instantaneous Spectral Imaging Öktem, Sevinç Figen; Davila, Joseph M (2014-12-01) Spectral imaging, the simultaneous imaging and spectroscopy of a radiating scene, is a fundamental diagnostic technique in the physical sciences with widespread application. Due to the intrinsic limitation of two-dimensional (2D) detectors in capturing inherently three-dimensional (3D) data, spectral imaging techniques conventionally rely on a spatial or spectral scanning process, which renders them unsuitable for dynamic scenes. In this paper, we present a nonscanning (instantaneous) spectral imaging techn...

Citation Formats

M. Sattari, “A Hybrid geo-activity recommendation system using advanced feature combination and semantic activity similarity,” M.S. - Master of Science, Middle East Technical University, 2013.