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A novel overlapping method to alleviate the cold-start problem in recommendation systems
(World Scientific, 2021) Al-Sabaawi, Ali Mohsin Ahmed; Karacan, Hacer; Yenice, Yusuf Erkan
Recommendation systems (RSs) are tools for interacting with large and complex information spaces. They provide a personalized view of such spaces, prioritizing items likely to be of interest to the user. The main objective of RSs is to tool up users with desired items that meet their preferences. A major problem in RSs is called: "cold-start"; it is a potential problem called so in computer-based information systems which comprises a degree of automated data modeling. Particularly, it concerns the issue in which the system cannot draw any inferences nor have it yet gathered sufficient information about users or items. Since RSs performance is substantially limited by cold-start users and cold-start items problems; this research study takes the route for a major aim to attenuate users' cold-start problem. Still in the process of researching, sundry studies have been conducted to tackle this issue by using clustering techniques to group users according to their social relations, their ratings or both. However, a clustering technique disregards a variety of users' tastes. In this case, the researcher has adopted the overlapping technique as a tool to deal with the clustering technique's defects. The advantage of the overlapping technique excels over others by allowing users to belong to multi-clusters at the same time according to their behavior in the social network and ratings feedback. On that account, a novel overlapping method is presented and applied. This latter is executed by using the partitioning around medoids (PAM) algorithm to implement the clustering, which is achieved by means of exploiting social relations and confidence values. After acquiring users' clusters, the average distances are computed in each cluster. Thereafter, a content comparison is made regarding the distances between every user and the computed distances of the clusters. If the comparison result is less than or equal to the average distance of a cluster, a new user is added to this cluster. The singular value decomposition plus (SVD++) method is then applied to every cluster to compute predictions values. The outcome is calculated by computing the average of mean absolute error (MAE) and root mean square error (RMSE) for every cluster. The model is tested by two real world datasets: Ciao and FilmTrust. Ultimately, findings have exhibited a great deal of insights on how the proposed model outperformed a number of the state-of-the-art studies in terms of prediction accuracy.
Adaptive beam-size control scheme for ground-to-satellite optical communications
(Society of Photo-Optical Instrumentation Engineers, Bellingham, WA, United States, 1999) Yenice, Yusuf Erkan; Evans, Berry G.
Atmospheric turbulence severely degrades the performance of ground-to-satellite optical links. Employment of adaptive optics to enhance ground-to-space optical communication systems has recently been considered and possible benefits have been shown. Uplink scintillation reduction using multiple transmitters is also being considered. What appears to be currently missing in such work is the realization that transmitter beam size is a crucial design parameter and its optimum value changes continuously according to changing turbulence conditions along the propagation path. We emphasize this point and propose a configuration in which the uplink transmitter beam size is controlled in real time in response to measured turbulence parameters to maximize mean intensity and minimize fluctuations on the satellite receiver. The full analytical evaluation is not tractable, but semianalytic simulations can be run to explore the improvement for different scenarios and site conditions. Some preliminary simulation results are presented and the difficulties hindering the achievement of more meaningful results through simulation are discussed. Controlling the beam size, especially by a factor of 2 or so, in relatively long time scales should not be a problem. The technology is sufficient to design an experiment to prove its feasibility.
Exploiting implicit social relationships via dimension reduction to improve recommendation system performance
(Public Library of Science, 2020) Ahmed Al-Sabaawi, Ali M.; Karacan, Hacer U.; Yenice, Yusuf Erkan
The development of Web 2.0 and the rapid growth of available data have led to the development of systems, such as recommendation systems (RSs), that can handle the information overload. However, RS performance is severely limited by sparsity and cold-start problems. Thus, this paper aims to alleviate these problems. To realize this objective, a new model is proposed by integrating three sources of information: a user-item matrix, explicit and implicit relationships. The core strategy of this study is to use the multi-step resource allocation (MSRA) method to identify hidden relations in social information. First, explicit social information is used to compute the similarity between each pair of users. Second, for each non-friend pair of users, the MSRA method is applied to determine the probability of their relation. If the probability exceeds a threshold, a new relationship will be established. Then, all sources are incorporated into the Singular Value Decomposition (SVD) method to compute the missing prediction values. Furthermore, the stochastic gradient descent technique is applied to optimize the training process. Additionally, two real datasets, namely, Last.Fm and Ciao, are utilized to evaluate the proposed method. In terms of accuracy, the experiment results demonstrate that the proposed method outperforms eight state-of-the-art approaches: Heats, PMF, SVD, SR, EISR-JC, EISR-CN, EISR-PA and EISR-RAI.
Higher order annular Gaussian laser beam propagation in free space
(2006) Eyyubo?lu, Halil Tanyer; Yenice, Yusuf Erkan; Baykal, Yahya Kemal
Propagation of higher order annular Gaussian (HOAG) laser beams in free space is examined. HOAG beams are defined as the difference of two Hermite-Gaussian (HG) beams; thus, they can be produced by subtracting a smaller beam from a larger beam, that are cocentered and both possess HG mode field distributions. Such beams can be considered as a generalization of the well-known annular Gaussian beams. We formulate the source and receiver plane characteristics and kurtosis parameter of HOAG beams propagating in free space and evaluate them numerically. In comparison to HG beams, HOAG beams have a broader beam size with outer lobes of kidney shape. The amount of received power within the same receiver aperture size, that is, power in bucket, is generally lower for higher order beams. The convergence of the kurtosis parameter to an asymptotic value for higher order beams takes much longer propagation distances compared to zero-order beams. © 2006 Society of Photo-Optical Instrumentation Engineers.
Kırılma indisi yapı parametresinin olasılık dağılımı
(IEEE, 2017) Yazar, İbrahim; Yenice, Yusuf Erkan; Sarı, Filiz
Bina dışı kablosuz optik haberleşme sistemlerinin analiz ve tasarımı için en önemli parametre olan kırılma indisi yapı parametresinin olasılık yoğunluk fonksiyonunu belirleyen herhangi bir teorik temel bulunmayıp, uygulamada lognormal veya beta dağılımlarından biri tercih edilmektedir. Bu çalışmada kamuya açık bir veri kümesi, Pearson sınıflandırması ve momentler yöntemi kullanılarak, olasılık dağılımının lognormal dağılımdaki gibi sadece tek taraftan veya beta dağılımındaki gibi iki taraftan sınırlı olup olmadığı araştırılmış ve iki taraftan da sınırlı olduğu yönünde ipuçları elde edilmiştir.
Lorentz-Gaussian beam performance for weak turbulence
(Institute of Electrical and Electronics Engineers Inc., 2016) Sarı, Filiz; Yenice, Yusuf Erkan
Average BER-SNR variations of Lorentz-Gaussian laser beam are analyzed for terrestrial optical wireless communications. Using the scintillation index obtained by the extended Huygens-Fresnel method, BER-SNR variations are evaluated for weak turbulence. It is shown that collimated and focused Lorentz-Gaussian beams have better link performance compared to pure Gaussian beams for specified parameter realms. © 2016 IEEE.
Optimum beam size for laser beam propagating through atmospheric turbulence
(1999) Yenice, Yusuf Erkan; Evans, Barry G.
A previous study concluded that the optimum beam diameter for a laser beam propagating through atmospheric turbulence is of the order of the coherence scale. It is shown that the optimum size is critically dependent on beam wander and pointing accuracy, and can be much smaller. Consequently, the beam size maximising mean intensity may not coincide with the size minimising fluctuations, and a compromise may be necessary. © IEE: 1999.
Probability distribution of refractive index structure parameter
(Institute of Electrical and Electronics Engineers Inc., 2017) Yazar, İbrahim; Yenice, Yusuf Erkan; Sarı, Filiz
As no theoretical justification exists for probability density function of refractive index structure parameter, which is the most important parameter for analysis and design of outdoor optical wireless communication systems, either lognormal or beta distribution is preferred in practice. In this work, whether the distribution is semi-infinite as in lognormal distribution or bounded on both sides as in beta distribution is investigated by using a publicly accessible data set, Pearson distribution system and the method of moments, and first hints indicating double boundedness are achieved. © 2017 IEEE.
Propagation of cross beams through atmospheric turbulence
(2006) Yenice, Yusuf Erkan; Eyyubo?lu, Halil Tanyer; Baykal, Yahya K.
Propagation properties of cross beam in turbulent medium are studied. A cross beam is constructed by the sum of two highly asymmetric Gaussian beams placed along transverse axes. It is known that such beams, when propagating in free space, will exhibit contrasting diffraction behaviours; they expand widely in one axis, while they are almost non-diffracting in the other axis within useful link lengths. This behaviour allows detecting the two components and a sum component if desired separately with a practical multiaperture receiver. Bearing in mind that this property can be exploited for a diversity scheme, our present work focuses on the propagation of such beams in turbulent atmosphere. To this end, starting with a source field expression of the cross beam, the second order mutual coherence function is formulated at the receiver plane. Intensity plots describing the dependence on the source and propagation parameters on the receiver plane are provided. The results tend to confirm the applicability of the concept provided the design parameters are appropriately chosen. For a decisive assessment, however, turbulence-induced beam wander must also be examined.
SVD++ and clustering approaches to alleviating the cold-start problem for recommendation systems
(ICIC International, 2021) Al-Sabaawi, Ali Mohsin Ahmed; Karacan, Hacer; Yenice, Yusuf Erkan
Recommendation systems provide a solution to tackle information overload problem. These systems have several limitations, one of which is cold-start users. In this article, a new method is proposed to overcome the cold-start user problem. The main idea of this study is to apply a clustering technique using trust relations and rating information to compute the weights. First, the implicit relations are determined, and then the similarity is computed for each pair of explicit and implicit relations. Second, confidence values are determined through an information rating by dividing the number of common items for each pair of users by the number of items that have been rated by the first user of this pair. Furthermore, the similarity and confidence values are integrated to produce weight values, and then the distance values are inferred. Additionally, the partitioning around medoids clustering algorithm is adopted to cluster the users into groups according to their computed distances. Moreover, the Singular Value Decomposition Plus (SVD++) method is employed for each cluster to predict the items for cold-start users. Eventually, the proposed method is evaluated with two real-world datasets. The results reveal that the proposed method outperforms the state-of-the-art trust methods in terms of prediction accuracy.
Two models based on social relations and SVD++ method for recommendation system
(International Association of Online Engineering, 2021) Al Sabaawi, Ali M. Ahmed; Karacan, Hacer; Yenice, Yusuf Erkan
Recently, Recommender Systems (RSs) have attracted many researchers whose goal is to improve the performance of the prediction accuracy of recommendation systems by alleviating RSs drawbacks. The most common limitations are sparsity and the cold-start user problems. This article proposes two models to mitigate the effects of these limitations. The proposed models exploit five sources of information: rating information, which involves two sources, namely explicit and implicit, which can be extracted via users’ ratings, and two types of social relations: explicit and implicit relations, the last source is confidence values that are included in the first model only. The whole sources are combined into the Singular Value Decomposition plus (SVD++) method. First, to extract implicit relations, each non-friend pair of users, the Multi-Steps Resource Allocation (MSRA) method is adopted to compute the probability of being friends. If the probability has accepted value which exceeds a threshold, an implicit relationship will be created. Second, the similarity of explicit and implicit social relationships for each pair of users is computed. Regarding the first model, a confidence value between each pair of users is computed by dividing the number of common items by the total number of items which have also rated by the first user of this pair. The confidence values are combined with the similarity values to produce the weight factor. Furthermore, the weight factor, explicit, and implicit feedback information are integrated into the SVD++ method to compute the missing prediction values. Additionally, three standard datasets are utilized in this study, namely Last. Fm, Ciao, and FilmTrust, to evaluate our models. The experimental results have revealed that the proposed models outperformed state-of-the-art approaches in terms of accuracy.

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