Detection of Review Abuse via Semi-Supervised Binary Multi-Target Tensor Decomposition

Product reviews and ratings on e-commerce websites provide customers with detailed insights about various aspects of the product such as quality, usefulness, etc. Since they influence customers' buying decisions, product reviews have become a fertile ground for abuse by sellers (colluding with reviewers) to promote their own products or to tarnish the reputation of competitor's products. In this paper, our focus is on detecting such abusive entities (both sellers and reviewers) by applying tensor decomposition on the product reviews data. While tensor decomposition is mostly unsupervised, we formulate our problem as a semi-supervised binary multi-target tensor decomposition, to take advantage of currently known abusive entities. We empirically show that our multi-target semi-supervised model achieves higher precision and recall in detecting abusive entities as compared to unsupervised techniques. Finally, we show that our proposed stochastic partial natural gradient inference for our model empirically achieves faster convergence than stochastic gradient and Online-EM with sufficient statistics.Comment: Accepted to the 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2019. Contains supplementary material. arXiv admin note: text overlap with arXiv:1804.0383

Power-hop: A pervasive observation for real complex networks

Complex networks have been shown to exhibit universal properties, with one of the most consistent patterns being the scale-free degree distribution, but are there regularities obeyed by the r-hop neighborhood in real networks? We answer this question by identifying another power-law pattern that describes the relationship between the fractions of node pairs C(r) within r hops and the hop count r. This scale-free distribution is pervasive and describes a large variety of networks, ranging from social and urban to technological and biological networks. In particular, inspired by the definition of the fractal correlation dimension D2 on a point-set, we consider the hop-count rto be the underlying distance metric between two vertices of the network, and we examine the scaling of C(r) with r. We find that this relationship follows a power-law in real networks within the range 2<r<d, where d is the effective diameter of the network, that is, the 90-th percentile distance. We term this relationship as power-hop and the corresponding power-law exponent as power-hop exponent h. We provide theoretical justification for this pattern under successful existing network models, while we analyze a large set of real and synthetic network datasets and we show the pervasiveness of the power-hop

Optimizing patient risk stratification for colonoscopy screening and surveillance of colorectal cancer: The role for linked data

No abstract available for this article

Unsupervised user behavior representation for fraud review detection with cold-start problem

© Springer Nature Switzerland AG 2019. Detecting fraud review is becoming extremely important in order to provide reliable information in cyberspace, in which, however, handling cold-start problem is a critical and urgent challenge since the case of cold-start fraud review rarely provides sufficient information for further assessing its authenticity. Existing work on detecting cold-start cases relies on the limited contents of the review posted by the user and a traditional classifier to make the decision. However, simply modeling review is not reliable since reviews can be easily manipulated. Also, it is hard to obtain high-quality labeled data for training the classifier. In this paper, we tackle cold-start problems by (1) using a user’s behavior representation rather than review contents to measure authenticity, which further (2) consider user social relations with other existing users when posting reviews. The method is completely (3) unsupervised. Comprehensive experiments on Yelp data sets demonstrate our method significantly outperforms the state-of-the-art methods

Reduction of neurovascular damage resulting from microelectrode insertion into the cerebral cortex using

Penetrating neural probe technologies allow investigators to record electrical signals in the brain. The implantation of probes causes acute tissue damage, partially due to vasculature disruption during probe implantation. This trauma can cause abnormal electrophysiological responses and temporary increases in neurotransmitter levels, and perpetuate chronic immune responses. A significant challenge for investigators is to examine neurovascular features below the surface of the brain in vivo. The objective of this study was to investigate localized bleeding resulting from inserting microscale neural probes into the cortex using two-photon microscopy (TPM) and to explore an approach to minimize blood vessel disruption through insertion methods and probe design. 3D TPM images of cortical neurovasculature were obtained from mice and used to select preferred insertion positions for probe insertion to reduce neurovasculature damage. There was an 82.8 ± 14.3% reduction in neurovascular damage for probes inserted in regions devoid of major (>5 µm) sub-surface vessels. Also, the deviation of surface vessels from the vector normal to the surface as a function of depth and vessel diameter was measured and characterized. 68% of the major vessels were found to deviate less than 49 µm from their surface origin up to a depth of 500 µm. Inserting probes more than 49 µm from major surface vessels can reduce the chances of severing major sub-surface neurovasculature without using TPM.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85401/1/7_4_046011.pd

Growth performance, fatty acid profile and lipid oxidative stability of breast muscle in chickens fed probiotics and antibiotics or their mixture

This study assessed the effects of dietary supplementation of probiotics, antibiotics and an antibiotic-probiotics mixture on growth performance of broilers, and the fatty acid profile and oxidative stability of broiler breast muscle. A total of 480 one-day-old broiler chicks (Cobb 500) were assigned to four treatment groups and fed for 42 days. The basal diet served as control treatment (Diet 1), while chicks assigned to Diets 2, 3 and 4 were fed the basal diet with the addition of 0.1 mg/kg of an antibiotic growth promoter (AGP), a commercial probiotic 5 g/kg or the AGP (0.1 mg/kg) + the commercial probiotic (5 g/kg), respectively. Feed intake, weight gain and feed conversion ratio were determined. Fatty acid (FA) profile and lipid oxidative status were monitored at 1 and 7 days post mortem. The results showed no significant difference in average bodyweights among the treatments. However, birds fed Diets 3 and 4 had significantly lower feed conversion ratios and feed intake than the other treatments. At day 7 post mortem, the lipid oxidation in breast meat was significantly lower in Diet 3 compared with the other diets. The meat of the birds fed Diet 3 had lower oleic acid, but higher palmitic acid concentrations at 1 day post mortem. At 1 day postmortem the polyunsaturated fatty acid to saturated fatty acid (PUFA : SFA) ratio was significantly lower in the breast muscle of birds fed Diet 3 compared with those fed Diets 1 and 4, but increased at 7 days postmortem. It could be concluded that probiotics supplementation showed high potential to improve oxidative stability, thereby increasing the shelf life of chicken meat

Transcriptional and biochemical analyses of gibberellin expression and content in germinated barley grain

Mobilization of reserves in germinated cereal grains is critical for early seedling vigour, global crop productivity and hence food security. Gibberellins (GAs) are central to this process. We have developed a spatio-temporal model that describes the multifaceted mechanisms of GA regulation in germinated barley grain. The model was generated using RNA-seq transcript data from tissues dissected from intact, germinated grain, which closely match measurements of GA hormones and their metabolites in those tissues. The data show that successful grain germination is underpinned by high concentrations of GA precursors in ungerminated grain, the use of independent metabolic pathways for the synthesis of several bioactive GAs during germination, and a capacity to abort bioactive GA biosynthesis. The most abundant bioactive form is GA₁, which is synthesized in the scutellum as a glycosyl conjugate that diffuses to the aleurone, where it stimulates de novo synthesis of a GA₃ conjugate and GA₄. Synthesis of bioactive GAs in the aleurone provides a mechanism that ensures the hormonal signal is relayed from the scutellum to the distal tip of the grain. The transcript dataset of 33,421 genes used to define GA metabolism is available as a resource to analyse other physiological processes in germinated grain.Natalie S. Betts, Christoph Dockter, Oliver Berkowitz, Helen M. Collins, Michelle Hooi, Qiongxian Lu, Rachel A. Burton, Vincent Bulone, Birgitte Skadhauge, James Whelan, and Geoffrey B. Finche