scholarly journals Sequential Recommender System based on Hierarchical Attention Networks

2018 ◽  
Author(s):  
Haochao Ying ◽  
Fuzhen Zhuang ◽  
Fuzheng Zhang ◽  
Yanchi Liu ◽  
Guandong Xu ◽  
...  
Keyword(s):  
Experimental Study ◽  
State Of The Art ◽  
Short Term ◽  
Activity Data ◽  
Sequential Behavior ◽  
Attention Networks ◽  
Item Representation ◽  
Item Item ◽  
Over Time

With a large amount of user activity data accumulated, it is crucial to exploit user sequential behavior for sequential recommendations. Conventionally, user general taste and recent demand are combined to promote recommendation performances. However, existing methods often neglect that user long-term preference keep evolving over time, and building a static representation for user general taste may not adequately reflect the dynamic characters. Moreover, they integrate user-item or item-item interactions through a linear way which limits the capability of model. To this end, in this paper, we propose a novel two-layer hierarchical attention network, which takes the above properties into account, to recommend the next item user might be interested. Specifically, the first attention layer learns user long-term preferences based on the historical purchased item representation, while the second one outputs final user representation through coupling user long-term and short-term preferences. The experimental study demonstrates the superiority of our method compared with other state-of-the-art ones.

The Short-Term and Long-Term Impacts of Sarbanes-Oxley Act on Composition and Characteristics of Corporate Board of Directors

2015 ◽  
Vol 5 (4) ◽  
Author(s):  
Halil Kaya ◽  
Gaurango Banerjee
Keyword(s):  
Board Composition ◽  
Corporate Boards ◽  
Corporate Accountability ◽  
Corporate Board ◽  
Short Term ◽  
Dual Roles ◽  
Board Characteristics ◽  
Sarbanes Oxley ◽  
Over Time

The paper examines the Sarbanes-Oxley (2002) Acts immediate impact on board composition and characteristics as well as possible reversals in its impact over time. Effects on directors age and tenure are analyzed over the 2001-06 sample period. Female participation in corporate boards is also studied in the pre-SOX and post-SOX periods. The dual roles of directors in being a member of the board as well as serving as either CEO, CFO, Chairman, Co-Chair, Founder, or Lead Director of their respective companies is also examined. We observe a short-term impact of SOX on board compositions due to changes seen in board characteristics between 2001 (pre-SOX), and 2003-05 short-term period (post-SOX). Also, we observe a reversal of board characteristics in 2006 to pre-SOX levels implying that the effects of SOX on board composition were short-lived, and needs to be monitored over time to ensure adherence to corporate accountability guidelines over the long-term.

scholarly journals Personality dynamics at work: The effects of form, time, and context of variability

2021 ◽  
pp. 089020702110173
Author(s):  
Nadin Beckmann ◽  
Damian P Birney ◽  
Amirali Minbashian ◽  
Jens F Beckmann
Keyword(s):  
Individual Differences ◽  
Cognitive Ability ◽  
Temporal Stability ◽  
Limited Evidence ◽  
Short Term ◽  
State Data ◽  
The Status ◽  
Over Time ◽  
Trait Variability

The study aimed to investigate the status of within-person state variability in neuroticism and conscientiousness as individual differences constructs by exploring their (a) temporal stability, (b) cross-context consistency, (c) empirical links to selected antecedents, and (d) empirical links to longer term trait variability. Employing a sample of professionals ( N = 346) from Australian organisations, personality state data together with situation appraisals were collected using experience sampling methodology in field and repeatedly in lab-like settings. Data on personality traits, cognitive ability, and motivational mindsets were collected at baseline and after two years. Contingent (situation contingencies) and non-contingent (relative SD) state variability indices were relatively stable over time and across contexts. Only a small number of predictive effects of state variability were observed, and these differed across contexts. Cognitive ability appeared to be associated with state variability under lab-like conditions. There was limited evidence of links between short-term state and long-term trait variability, except for a small effect for neuroticism. Some evidence of positive manifold was found for non-contingent variability. Systematic efforts are required to further elucidate the complex pattern of results regarding the antecedents, correlates and outcomes of individual differences in state variability.

scholarly journals Investigating the Broken-Heart Effect: a Model for Short-Term Dependence between the Remaining Lifetimes of Joint Lives

2012 ◽  
Vol 7 (2) ◽  
pp. 236-257 ◽  
Author(s):  
Jaap Spreeuw ◽  
Iqbal Owadally
Keyword(s):  
Mortality Rates ◽  
Short Term ◽  
Numerical Work ◽  
Data Set ◽  
Multiple State ◽  
Multiple State Model ◽  
Insurance Data ◽  
Over Time ◽  
Assurance Contracts

AbstractWe analyze the mortality of couples by fitting a multiple state model to a large insurance data set. We find evidence that mortality rates increase after the death of a partner and, in addition, that this phenomenon diminishes over time. This is popularly known as a “broken-heart” effect and we find that it affects widowers more than widows. Remaining lifetimes of joint lives therefore exhibit short-term dependence. We carry out numerical work involving the pricing and valuation of typical contingent assurance contracts and of a joint life and survivor annuity. If insurers ignore dependence, or mis-specify it as long-term dependence, then significant mis-pricing and inappropriate provisioning can result. Detailed numerical results are presented.

scholarly journals Macroeconomic Synchronization Between G3 Countries

2002 ◽  
Vol 3 (2) ◽  
pp. 137-153 ◽  
Author(s):  
Amado Peirό
Keyword(s):  
Business Cycle ◽  
Interest Rates ◽  
Short Term ◽  
The Us ◽  
Production Prices ◽  
Over Time

AbstractThis paper studies the existence of a world business cycle by examining quarterly and annual comovements in production, prices and interest rates in the three main world economies: Germany, Japan and the US. In accordance with earlier studies, contemporaneous relationships clearly dominate short-term dynamics. The evidence indicates the existence of strong comovements in prices and long-term interest rates, and, to a lesser degree, in GDP and short-term interest rates. They are, however, rather unstable over time.

scholarly journals Disentangling niche theory and beta diversity change

2021 ◽  
Author(s):  
William Godsoe ◽  
Peter J Bellingham ◽  
Elena Moltchanova
Keyword(s):  
Beta Diversity ◽  
Price Equation ◽  
Short Term ◽  
Before And After ◽  
Environmental Requirements ◽  
Habitat Specialists ◽  
Montane Tropical Forest ◽  
Ecological Drift ◽  
Over Time

Beta diversity describes the differences in species composition among communities. Changes in beta diversity over time are thought to be due to selection based on species' niche characteristics. For example, theory predicts that selection that favours habitat specialists will increase beta diversity. In practice, ecologists struggle to predict how beta diversity changes. To remedy this problem, we propose a novel solution that formally measures selection's effects on beta diversity. Using the Price equation, we show how change in beta diversity over time can be partitioned into fundamental mechanisms including selection among species, variable selection among communities, drift, and immigration. A key finding of our approach is that a species' short-term impact on beta diversity cannot be predicted using information on its long-term environmental requirements (i.e. its niche). We illustrate how our approach can be used to partition causes of diversity change in a montane tropical forest before and after an intense hurricane. Previous work in this system highlighted the resistance of habitat specialists and the recruitment of light-demanding species but was unable to quantify the importance of these effects on beta diversity. Using our approach, we show that changes in beta diversity were consistent with ecological drift. We use these results to highlight the opportunities presented by a synthesis of beta diversity and formal models of selection.

scholarly journals Learning Long- and Short-Term User Literal-Preference with Multimodal Hierarchical Transformer Network for Personalized Image Caption

2020 ◽  
Vol 34 (05) ◽  
pp. 9571-9578 ◽  
Author(s):  
Wei Zhang ◽  
Yue Ying ◽  
Pan Lu ◽  
Hongyuan Zha
Keyword(s):  
State Of The Art ◽  
Natural Extension ◽  
Target Image ◽  
Short Term ◽  
Image Representations ◽  
High Level ◽  
Image Descriptions ◽  
Shed Light ◽  
Image Caption

Personalized image caption, a natural extension of the standard image caption task, requires to generate brief image descriptions tailored for users' writing style and traits, and is more practical to meet users' real demands. Only a few recent studies shed light on this crucial task and learn static user representations to capture their long-term literal-preference. However, it is insufficient to achieve satisfactory performance due to the intrinsic existence of not only long-term user literal-preference, but also short-term literal-preference which is associated with users' recent states. To bridge this gap, we develop a novel multimodal hierarchical transformer network (MHTN) for personalized image caption in this paper. It learns short-term user literal-preference based on users' recent captions through a short-term user encoder at the low level. And at the high level, the multimodal encoder integrates target image representations with short-term literal-preference, as well as long-term literal-preference learned from user IDs. These two encoders enjoy the advantages of the powerful transformer networks. Extensive experiments on two real datasets show the effectiveness of considering two types of user literal-preference simultaneously and better performance over the state-of-the-art models.

scholarly journals Learning from Interventions Using Hierarchical Policies for Safe Learning

2020 ◽  
Vol 34 (06) ◽  
pp. 10352-10360
Author(s):  
Jing Bi ◽  
Vikas Dhiman ◽  
Tianyou Xiao ◽  
Chenliang Xu
Keyword(s):  
Reaction Time ◽  
State Of The Art ◽  
The State ◽  
Policy Framework ◽  
Asymptotic Performance ◽  
Short Term ◽  
Learning From Demonstrations ◽  
Hierarchical Levels ◽  
Long Term Behavior

Learning from Demonstrations (LfD) via Behavior Cloning (BC) works well on multiple complex tasks. However, a limitation of the typical LfD approach is that it requires expert demonstrations for all scenarios, including those in which the algorithm is already well-trained. The recently proposed Learning from Interventions (LfI) overcomes this limitation by using an expert overseer. The expert overseer only intervenes when it suspects that an unsafe action is about to be taken. Although LfI significantly improves over LfD, the state-of-the-art LfI fails to account for delay caused by the expert's reaction time and only learns short-term behavior. We address these limitations by 1) interpolating the expert's interventions back in time, and 2) by splitting the policy into two hierarchical levels, one that generates sub-goals for the future and another that generates actions to reach those desired sub-goals. This sub-goal prediction forces the algorithm to learn long-term behavior while also being robust to the expert's reaction time. Our experiments show that LfI using sub-goals in a hierarchical policy framework trains faster and achieves better asymptotic performance than typical LfD.

scholarly journals Long-term target tracking combined with re-detection

2020 ◽  
Author(s):  
Juanjuan Wang ◽  
HaoRan Yang ◽  
Ning Xu ◽  
Chengqin Wu ◽  
ZengShun Zhao ◽  
...  
Keyword(s):  
Correlation Energy ◽  
State Of The Art ◽  
Tracking Algorithm ◽  
Correlation Filters ◽  
Short Term ◽  
Tracking Method ◽  
Tracking Tasks ◽  
Svm Model ◽  
Confidence Degree

Abstract The long-term visual tracking undergoes more challenges and is closer to realistic applications than short-term tracking. However, the performances of most existing methods have been limited in the long-term tracking tasks. In this work, we present a reliable yet simple long-term tracking method, which extends the state-of-the-art Learning Adaptive Discriminative Correlation Filters (LADCF) tracking algorithm with a re-detection component based on the SVM model. The LADCF tracking algorithm localizes the target in each frame and the re-detector is able to efficiently re-detect the target in the whole image when the tracking fails. We further introduce a robust confidence degree evaluation criterion that combines the maximum response criterion and the average peak-to correlation energy (APCE) to judge the confidence level of the predicted target. When the confidence degree is generally high, the SVM is updated accordingly. If the confidence drops sharply, the SVM re-detects the target. We perform extensive experiments on the OTB-2015 and UAV123 datasets. The experimental results demonstrate the effectiveness of our algorithm in long-term tracking.

Really Rewarding Rewards: Strategic Licensing in Long-Term Healthy Food Consumption

2021 ◽  
Author(s):  
Rishika Rishika ◽  
Sven Feurer ◽  
Kelly L Haws
Keyword(s):  
Decision Making ◽  
Experimental Study ◽  
Consumption Patterns ◽  
Driving Mechanism ◽  
Policy Makers ◽  
Calorie Consumption ◽  
Food Purchases ◽  
Related Aspect ◽  
Over Time

Abstract Licensing is a well-documented form of justifying individual indulgent choices, but less is known about how licensing affects food decision-making patterns over time. Accordingly, we examine whether consumers incorporate licensing strategically and deliberately in their long-term consumption patterns and identify reward programs as a context in which strategic licensing is likely to occur. We propose that members with lower-calorie consumption patterns strategically indulge more on reward purchase occasions, and that forethought is required for such an effect to occur. A longitudinal study analyzing 272,677 real food purchases made by 7,828 consumers over a 14-month period provides striking evidence of our key proposition. An exploration of the inter-purchase time-related aspect of purchase acceleration suggests that forethought on behalf of consumers is necessary for strategic licensing to occur. A subsequent experimental study (N = 605) comprising five consecutive choice occasions provides additional evidence of forethought by demonstrating that strategic licensing occurs only when expected (but not windfall reward) occasions are involved, and by showing that anticipated negative affect for not indulging is the driving mechanism. We conclude with a discussion of the implications of our results for consumers, managers, and public policy makers.

A Checklist for a New Millennium School Science Department

2011 ◽  
pp. 273-274
Author(s):  
Ed Hessler
Keyword(s):  
Professional Development ◽  
Teacher Preparation ◽  
Student Learning ◽  
School Science ◽  
Learning Science ◽  
Science Department ◽  
Short Term ◽  
Over Time ◽  
New Millennium

My focus is both narrow and incomplete, for it is limited to a single area of learning: science, and it is in the form of a working list, a beginning of things one might write down, not in any particular order—so that they might be remembered and edited over time, with colleagues. Improving schools, teacher preparation, and professional development are important national priorities as we enter a new millennium. Past emphasis on targeted innovations in the short term are now conceptualized into the idea of continuous improvements that are connected in the long term. Today, the idea of improvement itself is being challenged. “Improvement,” the term of the technocrat, is being recast in the context of student learning—that is, how can we educate our young or learners of any age?

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