Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction

Click-Through Rate prediction is an important task in recommender systems, which aims to estimate the probability of a user to click on a given item. Recently, many deep models have been proposed to learn low-order and high-order feature interactions from original features. However, since useful interactions are always sparse, it is difficult for DNN to learn them effectively under a large number of parameters. In real scenarios, artificial features are able to improve the performance of deep models (such as Wide & Deep Learning), but feature engineering is expensive and requires domain knowledge, making it impractical in different scenarios. Therefore, it is necessary to augment feature space automatically. In this paper, We propose a novel Feature Generation by Convolutional Neural Network (FGCNN) model with two components: Feature Generation and Deep Classifier. Feature Generation leverages the strength of CNN to generate local patterns and recombine them to generate new features. Deep Classifier adopts the structure of IPNN to learn interactions from the augmented feature space. Experimental results on three large-scale datasets show that FGCNN significantly outperforms nine state-of-the-art models. Moreover, when applying some state-of-the-art models as Deep Classifier, better performance is always achieved, showing the great compatibility of our FGCNN model. This work explores a novel direction for CTR predictions: it is quite useful to reduce the learning difficulties of DNN by automatically identifying important features

Porphyrin‐Based Organophotocatalysts

The planar geometric structure and the rich absorption feature endow porphyrins with interesting optoelectronic properties and also make it promising building blocks for supramolecular assembly. Recent advances in the photocatalytic applications of porphyrins, including homogeneous, heterogeneous photocatalysis, and photoelectrochemical solar cells are highlighted. Porphyrin photocatalysts are involved in the form of molecules, supported molecules, nanostructures, and thin film. Related rational design strategies are provided for each form with an aim to enhance the light conversion efficiency. Finally, the ongoing directions and challenges for the future development of porphyrin semiconductors in high‐quality optoelectronic devices are also proposed

Tourist shopping behavior : a case of Shanghai outbound tourists / Yingzhi Guo...[et al.]

Shopping is an important tourist activity and its contribution to the economy is significant. For many visitors no trip is complete without having spent time shopping and tourists often feel they cannot return home without buying “something”. This research explored the basic shopping behaviour model of Shanghai outbound tourists. Data from 65 respondents were collected using the convenient sampling method. The motivations of Shanghai outbound tourists’ shopping behaviour were presented in seven dimensions including function, gift giving, affection, curiosity, scarcity, memory and cultural orientations. Quality, brand, shortage of specific goods in China’s domestic market, the lower price of goods in the outbound market and the convenient payments in the destinations are important attributes that spark their shopping behaviours. This outcome has at least had significant implications for tour operators and marketers to understand the needs of Chinese outbound tourists

Expression of TLR4-MyD88 and NF-κB in the Iris during Endotoxin-Induced Uveitis

Purpose. To observe the expression of Toll-like receptor-4 (TLR4), myeloid differentiation factor 88 (MyD88), and nuclear factor kappa B p65 (NF-κB p65) in iris tissue during endotoxin-induced uveitis (EIU) and evaluate the significance of these factors in uveitis. Methods. Wistar rats were randomly divided into 5 groups (0 h, 12 h, 24 h, 48 h, and 72 h, n = 10/group). Animal model of acute anterior uveitis was established by a hind footpad injection of 200 μg Cholera vibrio LPS. Expression of TLR4, MyD88, and NF-κB p65 in iris ciliary body tissue was detected through immunohistochemical staining. Results. Expression of TLR4 was not detected in normal iris-ciliary body complex, TLR4 positive cells with round morphology appeared in the iris stroma 12 hours after injection, significantly increased (P < .001) 48 hours after injection, and decreased gradually 72 hours after injection. Expression of MyD88 and NF-κB p65 is consistent with the change of the TLR4. Conclusions. The increased expression of TLR4 and its downstream signal transduction moleculesMyD88, NF-κB p65 indicate the potential role of pathway in the pathogenesis of acute anterior uveitis (AAU)

The Effect of Toll-Like Receptor 4 in the Aqueous Humor of Endotoxin-Induced Uveitis

In our previous study, we found that acute anterior uveitis (AAU) could be induced in wild-type mice (C3H/HeN), but it could not be induced in TLR4 gene-deficient mice (C3H/HeJ), we concluded that the translocation of transcription factor nuclear factor-κB (NF-κB) may play an important role. In this study, we examined the concentration of different cytokines in the aqueous humor of C3H/HeN mice and C3H/HeJ mice with the aim of exploring the role of different cytokines in the lipopolysaccharide (LPS) and TLR4-mediated signal transduction in the development of AAU