Within the thriving e-commerce landscape,some unscrupulous merchants hire spammer groups to post misleading reviews or ratings,aiming to manipulate public perception and disrupt fair market *** phenomenon has prompted...
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Within the thriving e-commerce landscape,some unscrupulous merchants hire spammer groups to post misleading reviews or ratings,aiming to manipulate public perception and disrupt fair market *** phenomenon has prompted a heightened research focus on spammer groups *** the e-commerce domain,current spammer group detection algorithms can be classified into three categories,i.e.,Frequent Item Mining-based,graph-based,and burst-based ***,existing graph-based algorithms have limitations in that they did not adequately consider the redundant relationships within co-review graphs and neglected to detect overlapping members within spammer *** address these issues,we introduce an overlapping spammer group detection algorithm based on deep reinforcement learning named ***,the algorithm filters out highly suspicious products and gets the set of reviewers who have reviewed these ***,taking these reviewers as nodes and their co-reviewing relationships as edges,we construct a homogeneous co-reviewing ***,to efficiently identify and handle the redundant relationships that are accidentally formed between ordinary users and spammer group members,we propose the Auto-Sim algorithm,which is a specifically tailored algorithm for dynamic optimization of the co-reviewing graph,allowing for adjustments to the reviewers’relationship network within the ***,candidate spammer groups are discovered by using the Ego-Splitting overlapping clustering algorithm,allowing overlapping members to exist in these ***,these groups are refined and ranked to derive the final list of spammer *** results based on real-life datasets show that our proposed DRL-OSG algorithm performs better than the baseline algorithms in Precision.
1 Introduction In recent years,the Massively Parallel Computation(MPC)model has gained significant ***,most of distributed and parallel graph algorithms in the MPC model are designed for static graphs[1].In fact,the g...
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1 Introduction In recent years,the Massively Parallel Computation(MPC)model has gained significant ***,most of distributed and parallel graph algorithms in the MPC model are designed for static graphs[1].In fact,the graphs in the real world are constantly *** size of the real-time changes in these graphs is smaller and more *** graph algorithms[2,3]can deal with graph changes more efficiently[4]than the corresponding static graph ***,most studies on dynamic graph algorithms are limited to the single machine ***,a few parallel dynamic graph algorithms(such as the graph connectivity)in the MPC model[5]have been proposed and shown superiority over their parallel static counterparts.
Deep CNNs are increasingly prevalent in various application domains such as image processing. To explain a CNN prediction, it is popular to employ occlusion-based explanations (OBE). OBE helps users understand which p...
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With the rapid development of social media, sentiment analysis from multimodal posts has garnered significant attention in recent years. However, the substantial size of these models impedes their deployment on resour...
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To address the issues of low accuracy and efficiency in water surface target detection caused by uneven lighting and water ripples, this study proposes a channel modeling-based DETR-like model. Starting from efficient...
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In this manuscript,we discuss the dynamical behavior of Chen-Lee-Liu(CLL)equation in birefringent fibers which is modeled by two-component nonlinear Schrodinger equation(NLSE)without four-wave mixing *** optical fiber...
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In this manuscript,we discuss the dynamical behavior of Chen-Lee-Liu(CLL)equation in birefringent fibers which is modeled by two-component nonlinear Schrodinger equation(NLSE)without four-wave mixing *** optical fibers and other wave-guide mediums this system models the propagation of soliton flow using group velocity dispersion(GVD)and self-steeping *** the realms of maritime transport,motion,and energy,the dynamics of deep-sea waves is one of oceanography’s greatest challenges.A mathematical model of the dynamics of solitary waves in the deep ocean under a twolayer stratification yields the NLSE,and resultantly,the interaction between the two can be described by a coupled *** two recently developed integration tools,namely the generalized exponential rational function method(GERFM)and the new extended direct algebraic method(NEDAM),the various optical pulses in the forms of bright,dark,combined,and complex solitons are ***,the hyperbolic,exponential,and trigonometric function solutions are *** addition,a comparison is made between our results and those that are well-known,and the study concludes that the solutions we’ve reached are *** choosing appropriate parameter values for numerical simulation and physical explanations,the significance of the results is *** results of this paper can enhance the nonlinear dynamical behavior of a given system and demonstrate the suitability of the methodology *** research,in our opinion,will be beneficial to a wide variety of engineering model specialists.
Accurate and timely access to the spatial distribution of crops is crucial for sustainable agricultural development and food security. However, extracting multi-crop areas based on high-resolution time-series data and...
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Teacher-student concentration in the teaching process is an essential indicator for evaluating teaching quality. Many researches assess students' learning interests by identifying their classroom behaviors but ign...
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A significant challenge in air quality index (AQI) prediction is to accurately evaluate the potential outcomes after conducting interventions in pollutant factors such as industrial emissions for each enterprise. Exis...
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Federated learning (FL) safeguards user privacy by uploading gradients instead of raw data. However, inference attacks can reconstruct raw data using gradients uploaded by users in FL. To mitigate this issue, research...
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