Solving the Cold-Start Problem in Recommender Systems with Social Tags

In this paper, based on the user-tag-object tripartite graphs, we propose a recommendation algorithm, which considers social tags as an important role for information retrieval. Besides its low cost of computational time, the experiment results of two real-world data sets, \emph{Del.icio.us} and \emph{MovieLens}, show it can enhance the algorithmic accuracy and diversity. Especially, it can obtain more personalized recommendation results when users have diverse topics of tags. In addition, the numerical results on the dependence of algorithmic accuracy indicates that the proposed algorithm is particularly effective for small degree objects, which reminds us of the well-known \emph{cold-start} problem in recommender systems. Further empirical study shows that the proposed algorithm can significantly solve this problem in social tagging systems with heterogeneous object degree distributions

Tag-Aware Recommender Systems: A State-of-the-Art Survey

In the past decade, Social Tagging Systems have attracted increasing attention from both physical and computer science communities. Besides the underlying structure and dynamics of tagging systems, many efforts have been addressed to unify tagging information to reveal user behaviors and preferences, extract the latent semantic relations among items, make recommendations, and so on. Specifically, this article summarizes recent progress about tag-aware recommender systems, emphasizing on the contributions from three mainstream perspectives and approaches: network-based methods, tensor-based methods, and the topic-based methods. Finally, we outline some other tag-related studies and future challenges of tag-aware recommendation algorithm

Polycystic ovary syndrome in patients with epilepsy: A study in 102 Chinese women

AbstractPurposeThe incidence of polycystic ovary syndrome (PCOS) increases in women with epilepsy (WWE), which appears to vary with ethnicity. This study was conducted to determine the incidence and risk factors of PCOS in Chinese WWE.MethodsThe study was carried out in 102 of 139 Chinese WWE at reproductive ages, with 32 receiving valproic acid (VPA), 40 receiving other antiepileptic drugs (AEDs), and 30 without AEDs therapy. PCOS was defined as having 2 or more of the following components: polycystic ovaries, hyperandrogenism, and amenorrhoea or oligomenorrhoea (a/oligomenorrhoea).ResultsOne or more isolated components of PCOS were found in 56 (54.9%) patients, with 29 (28.4%) having polycystic ovaries, 20 (19.6%) with a/oligomenorrhea, 7 (6.9%) with hyperandrogenism, and 13 (12.7%) with defined PCOS. Their average age at the start of seizure was 13.8±6.5years, younger than that of patients without these disorders (16.9±8.6years, p<0.05). VPA therapy increased the incidence of PCOS (11/32, 34.4%), in addition to increased blood levels of testosterone and luteinizing hormone (LH) as well as LH to FSH (follicle-stimulating hormone) ratio. No significant relationship was found between the incidence of PCOS and the type, duration, or frequency of seizures in these WWE.ConclusionThere is an increased incidence of PCOS in Chinese WWE at reproductive ages, by more than 2 times of that in the general population. Risk factors include seizures starting at a young age and VPA therapy

Creep behaviors and microstructural stabilities of Co-Al-W-Ta-Ti-based Superalloys

In last decade, the discovery of high-temperature stable γ\u27-Co3(Al, W) phase in Co-Al-W-base alloys motivated plentiful interests in designing the next generation γ\u27-strengthened Co-based superalloys. Continued efforts have been focused on increasing the γ\u27 solvus temperature and enhancing the γ/γ\u27 microstructural stability as well as improving the creep resistance at elevated temperatures in this class of superalloys. In the present work, the effects of Ti and Ta additions on the creep properties and the microstructural stabilities of Co-Al-W-Ta-Ti-based superalloys are investigated by means of integrated the experimental and computational approaches. The chemistry design of Co-Al-W-Ta-Ti alloys was supported by the thermodynamic calculations of phase stability using the Co-base alloys database in PandatTMdeveloped by the CALPHAD method. The atomic and the electronic structures for solute-strengthened (001) anti-phase boundaries (APB) of Co3(Al, TM) are investigated by first-principles calculations based on the density functional theory (DFT), where TM denotes transition metals. It is observed that at 1000oC, the creep property of a Co-based single-crystal superalloy containing Ti and Ta is superior in comparison with the other reported Co-Al-W-base single crystal alloys and the 1st generation commercial Ni-base single-crystal superalloys. The different creep behaviors between Co-based and Ni-based superalloys indicate that the creep deformation mechanism of Co-based superalloys is mainly associated with the stacking faults and anti-phase boundaries. Moreover, Co-Al-W-Ta-Ti model alloys have been developed with the variation of alloying additions, recently. Our designed alloys show better microstructural stability at higher temperature as well as high γ\u27 solvus temperature. DFT-based first principles calculations further reveal the complex electron structures induced by the variation of the lattice distortion around the fault layers in the solute-containing (001) APB. It is observed that the formation of the (001) APB in Co3Al changes the Co-centered deformation electron density isosurface from the typical tetrahedral shape in the FCC lattice into the “S” shape. With the segregation of solute atoms at (001) APB, the bond strength around the fault layers are increased by the electron redistribution by forming chemical bonds with Co, providing fundamental insights on interactions among alloying elements and their effects on APB and creep properties. The current study is helpful for continuous efforts on alloy design and development to improve temperature capability of γ\u27-strengthened Co-base superalloys

Collaborative filtering with diffusion-based similarity on tripartite graphs

Collaborative tags are playing more and more important role for the organization of information systems. In this paper, we study a personalized recommendation model making use of the ternary relations among users, objects and tags. We propose a measure of user similarity based on his preference and tagging information. Two kinds of similarities between users are calculated by using a diffusion-based process, which are then integrated for recommendation. We test the proposed method in a standard collaborative filtering framework with three metrics: ranking score, Recall and Precision, and demonstrate that it performs better than the commonly used cosine similarity.Comment: 8 pages, 4 figures, 1 tabl