Recruitment Market Trend Analysis with Sequential Latent Variable Models

Recruitment market analysis provides valuable understanding of industry-specific economic growth and plays an important role for both employers and job seekers. With the rapid development of online recruitment services, massive recruitment data have been accumulated and enable a new paradigm for recruitment market analysis. However, traditional methods for recruitment market analysis largely rely on the knowledge of domain experts and classic statistical models, which are usually too general to model large-scale dynamic recruitment data, and have difficulties to capture the fine-grained market trends. To this end, in this paper, we propose a new research paradigm for recruitment market analysis by leveraging unsupervised learning techniques for automatically discovering recruitment market trends based on large-scale recruitment data. Specifically, we develop a novel sequential latent variable model, named MTLVM, which is designed for capturing the sequential dependencies of corporate recruitment states and is able to automatically learn the latent recruitment topics within a Bayesian generative framework. In particular, to capture the variability of recruitment topics over time, we design hierarchical dirichlet processes for MTLVM. These processes allow to dynamically generate the evolving recruitment topics. Finally, we implement a prototype system to empirically evaluate our approach based on real-world recruitment data in China. Indeed, by visualizing the results from MTLVM, we can successfully reveal many interesting findings, such as the popularity of LBS related jobs reached the peak in the 2nd half of 2014, and decreased in 2015.Comment: 11 pages, 30 figure, SIGKDD 201

New approach to evaluate the TOWS matrix and its application in a mining company

SWOT analyses and the closely related TOWS matrix are frequent starting points for an organization to develop its strategy. The paper deals with the evaluation of the TOWS matrix and presents three novel approaches to evaluate the different factors of the TOWS matrix, namely (1) approach to evaluate the factors with identical weights; (2) approach to evaluate factors with their weights determined within the different quadrants of the TOWS matrix; and (3) approach to evaluate factors with weights determined within the whole TOWS matrix. The third approach has two variants. The proposed approaches to evaluate the TOWS matrix were tested on a SWOT analysis of a significant mining company in the Czech Republic. The results imply that the strategy W-T (weaknesses-threats) is recommended in three cases, while the strategy S-T (strengths-threats) is recommended once. The paper may be valuable for managers responsible for strategic planning.Web of Science118121303129