Conversational recommender systems (CRS) aim to recommend high-quality items users through interactive conversations. To develop an effective CRS, the support of datasets is essential. Existing CRS mainly focus on immediate requests from users, while lack proactive guidance recommendation scenario. In this paper, we contribute a new dataset named TG-ReDial (Recommendation Topic-Guided Dialog). Our has two major features. First, it incorporates topic threads enforce natural semantic...

Network Function Virtualization (NFV) is a promising technology that promises to significantly reduce the operational costs of network services by deploying virtualized functions (VNFs) commodity servers in place dedicated hardware middleboxes. The VNFs are typically running on virtual machine instances cloud infrastructure, where virtualization enables dynamic provisioning VNF instances, process fluctuating traffic needs go through service. In this paper, we target enterprise - expressed as...

ABSTRACT In recent years, researchers have increasingly sought batteries as an efficient and cost‐effective solution for energy storage supply, owing to their high density, low cost, environmental resilience. However, the issue of dendrite growth has emerged a significant obstacle in battery development. Excessive during charging discharging processes can lead short‐circuiting, degradation electrochemical performance, reduced cycle life, abnormal exothermic events. Consequently,...

Network function virtualization has emerged as a promising technology to enable rapid network service composition/innovation, energy conservation and cost minimization for operators. To optimally operate virtualized service, it is of key importance deploy VNF (virtualized function) chain within the provisioning infrastructure (e.g., servers cloud datacenter), dynamically scale in response flow traffic changes. Most existing work on scaling assume access precise bandwidth information...

With the rapid development of text categorization technology, there are still some problems, such as low classification efficiency, accuracy and incomplete extraction features, in case large amount data too many categorized attributes. In this paper, a hybrid model CNN (Convolutional Neural Network) BiLSTM (Bidirectional Long-term Short-term Memory combined with Attention (Attention Mechanism) is used to classify process long data. extracts feature information from text, then uses extract...

Link prediction is a task predicting whether there link between two nodes in network. Traditional methods that assume handcrafted features (such as common neighbors) the link’s formation mechanism are not universal. Other popular tend to learn representation, but they cannot represent fully. In this paper, we propose Edge-Nodes Representation Neural Machine (ENRNM), novel method which can abundant topological from network representation promote of link. The ENRNM learns by combining edge and...

Positive-unlabeled (PU) learning aims to train a classifier using the data containing only labeled-positive instances and unlabeled instances. However, existing PU methods are generally hard achieve satisfactory performance on trifurcate data, where positive distribute both sides of negative To address this issue, firstly we propose with asymmetric loss (PUAL), by introducing structure into objective function global local classifier. Then develop kernel-based algorithm enable PUAL obtain...

Most existing contrast enhancement methods obtain the maximum clipping point by iterations under a given PSNR/SSIM value, and perform backlight scaling to maintain image quality. However, they need high computational complexity determine optimal often cause over-saturation in images. In this paper, we propose scaled for LCDs without values using key-based compression. We automatically decomposition first decompose an into base detail layers bilateral filtering, then Finally, compensation...

Network Function Virtualization (NFV) is a promising technology that promises to significantly reduce the operational costs of network services by deploying virtualized functions (VNFs) commodity servers in place dedicated hardware middleboxes. The VNFs are typically running on virtual machine instances cloud infrastructure, where virtualization enables dynamic provisioning VNF instances, process fluctuating traffic needs go through service. In this paper, we target enterprise - expressed as...

The increased need for social communication has led to an increase in email users, and with it more spam is being spread. In this paper, by comparing exploring the accuracy of some supervised machine learning methods a deep method called Long short-term memory (LSTM) on problem classification, paper aims provide solutions filtering. This firstly conducts in-depth understanding analysis principles different algorithm models, which very helpful following research. Then experimental comparisons...

Names of classes/methods/variables play an important role in code readability. To investigate how developers choose names, Feitelson et al. conducted empirical survey and suggested a method to improve naming quality. We replicated their study, but limited the subjects university students. Specifically, we two experiments including 341 students from freshmen seniors. The aim first experiment was characteristics names given by experimental results showed that name length as well number words...

Coverage-based greybox fuzzing (CGF) has been approved to be effective in finding security vulnerabilities. Seed scheduling, the process of selecting an input as seed from pool for next iteration, plays a central role CGF. Although numerous scheduling strategies have proposed, most them treat these seeds independently and do not explicitly consider relationships among seeds. In this study, we make key observation that are valuable scheduling. We design propose "seed mutation tree" by...