Temporal Learning and Sequence Modeling for a Job Recommender System

We present our solution to the job recommendation task for RecSys Challenge 2016. The main contribution of our work is to combine temporal learning with sequence modeling to capture complex user-item activity patterns to improve job recommendations. First, we propose a time-based ranking model applied to historical observations and a hybrid matrix factorization over time re-weighted interactions. Second, we exploit sequence properties in user-items activities and develop a RNN-based recommendation model. Our solution achieved 5$^{th}$ place in the challenge among more than 100 participants. Notably, the strong performance of our RNN approach shows a promising new direction in employing sequence modeling for recommendation systems.Comment: a shorter version in proceedings of RecSys Challenge 201

Does quality drive employee satisfaction in the UK learning sector?

The purpose of this paper is to provide empirical evidence to assess the nature and extent of the link between employee satisfaction and organisational performance. This paper examines the link between staff satisfaction and organisational performance, presenting findings from 21 colleges of Further Education that have participated in both a survey of staff satisfaction (covering over 2,600 staff from these colleges) and in a diagnostic benchmarking exercise using the “Learning PROBE” methodology. The results suggest that whilst each of the measured aspects of work are regarded as being important by a majority of survey respondents, the level of “satisfaction” displayed in each of these attributes is indicated by only a minority of those surveyed. The findings support the existence of a link between staff satisfaction and organisational excellence. Staff satisfaction levels are most strongly associated with the leadership and service processes indices, and even more so with the overall organisational diagnosis. This suggests that colleges that are implementing “good practices” covering a range of managerial aspects, and who are achieving corresponding organisational results, are likely to be closer to satisfying their staff. Practices relating to people, performance management and organizational results also show association with staff's satisfaction gap, although not as significantly as above. The results suggest an holistic approach to implementing business practices appears to be more effective than concentrating only on deploying good practices in only a single area of the managerial process. The value of the paper is to the UK Further Education Sector in that it identifies those organisational practices, which improved, can in combination address to some extent the work satisfaction levels of their employees

Creating business value from big data and business analytics : organizational, managerial and human resource implications

This paper reports on a research project, funded by the EPSRC’s NEMODE (New Economic Models in the Digital Economy, Network+) programme, explores how organizations create value from their increasingly Big Data and the challenges they face in doing so. Three case studies are reported of large organizations with a formal business analytics group and data volumes that can be considered to be ‘big’. The case organizations are MobCo, a mobile telecoms operator, MediaCo, a television broadcaster, and CityTrans, a provider of transport services to a major city. Analysis of the cases is structured around a framework in which data and value creation are mediated by the organization’s business analytics capability. This capability is then studied through a sociotechnical lens of organization/management, process, people, and technology. From the cases twenty key findings are identified. In the area of data and value creation these are: 1. Ensure data quality, 2. Build trust and permissions platforms, 3. Provide adequate anonymization, 4. Share value with data originators, 5. Create value through data partnerships, 6. Create public as well as private value, 7. Monitor and plan for changes in legislation and regulation. In organization and management: 8. Build a corporate analytics strategy, 9. Plan for organizational and cultural change, 10. Build deep domain knowledge, 11. Structure the analytics team carefully, 12. Partner with academic institutions, 13. Create an ethics approval process, 14. Make analytics projects agile, 15. Explore and exploit in analytics projects. In technology: 16. Use visualization as story-telling, 17. Be agnostic about technology while the landscape is uncertain (i.e., maintain a focus on value). In people and tools: 18. Data scientist personal attributes (curious, problem focused), 19. Data scientist as ‘bricoleur’, 20. Data scientist acquisition and retention through challenging work. With regards to what organizations should do if they want to create value from their data the paper further proposes: a model of the analytics eco-system that places the business analytics function in a broad organizational context; and a process model for analytics implementation together with a six-stage maturity model

Republic of Ghana Country Strategy Paper 2012-2016

This report aims to propose a Bank Group's strategy for supporting Ghana's development efforts over the period 2012 -- 2016. Several factors make a new Bank country strategy for Ghana particularly timely at this moment. These include the enormous challenges the country still faces in its development trajectory in spite of its impressive growth in the last decade, the recent adoption by the Government of the "Ghana Shared Growth and Development Agenda" (GSGDA), the promising developments the country is experiencing in its economic prospects, including becoming an oil producer, attracting interest from BRICS, and the recent completion by the Bank and other development partners of a number of key knowledge products. All these combined provides an opportunity for the Bank and Ghana to lay the foundations for a renewed partnership

Looking Beyond the Bridge: How Temporary Agency Employment Affects Labor Market Outcomes

We perform a comprehensive analysis of the stepping-stone effect of temporary agency employment on unemployed workers. Using the timing-of-events approach, we not only investigate whether agency employment is a bridge into regular employment but also analyze its effect on post-unemployment wages and job stability for unemployed Danish workers. We find evidence of large positive treatment effects, particularly for immigrants. There is also some indication that higher treatment intensity increases the likelihood of leaving unemployment for regular jobs. Our results show that agency employment is even more effective in tight labor markets, where firms use agency employment primarily to screen potential candidates for permanent posts. Finally, our results suggest that agency employment may improve subsequent match quality in terms of wages and job duration.temporary agency employment; stepping stone; employment stability; wages

Anticipating Information Needs Based on Check-in Activity

In this work we address the development of a smart personal assistant that is capable of anticipating a user's information needs based on a novel type of context: the person's activity inferred from her check-in records on a location-based social network. Our main contribution is a method that translates a check-in activity into an information need, which is in turn addressed with an appropriate information card. This task is challenging because of the large number of possible activities and related information needs, which need to be addressed in a mobile dashboard that is limited in size. Our approach considers each possible activity that might follow after the last (and already finished) activity, and selects the top information cards such that they maximize the likelihood of satisfying the user's information needs for all possible future scenarios. The proposed models also incorporate knowledge about the temporal dynamics of information needs. Using a combination of historical check-in data and manual assessments collected via crowdsourcing, we show experimentally the effectiveness of our approach.Comment: Proceedings of the 10th ACM International Conference on Web Search and Data Mining (WSDM '17), 201

Looking Beyond the Bridge: How Temporary Agency Employment Affects Labor Market Outcomes

We perform a comprehensive analysis of the stepping-stone effect of temporary agency employment on unemployed workers. Using the timing-of-events approach, we not only investigate whether agency employment is a bridge into regular employment but also analyze its effect on post-unemployment wages and job stability for unemployed Danish workers. We find evidence of large positive treatment effects, particularly for immigrants. There is also some indication that higher treatment intensity increases the likelihood of leaving unemployment for regular jobs. Our results show that agency employment is even more effective in tight labor markets, where firms use agency employment primarily to screen potential candidates for permanent posts. Finally, our results suggest that agency employment may improve subsequent match quality in terms of wages and job duration.temporary agency employment, stepping stone, employment stability, wages