Learning from Multi-View Multi-Way Data via Structural Factorization Machines

Real-world relations among entities can often be observed and determined by different perspectives/views. For example, the decision made by a user on whether to adopt an item relies on multiple aspects such as the contextual information of the decision, the item's attributes, the user's profile and the reviews given by other users. Different views may exhibit multi-way interactions among entities and provide complementary information. In this paper, we introduce a multi-tensor-based approach that can preserve the underlying structure of multi-view data in a generic predictive model. Specifically, we propose structural factorization machines (SFMs) that learn the common latent spaces shared by multi-view tensors and automatically adjust the importance of each view in the predictive model. Furthermore, the complexity of SFMs is linear in the number of parameters, which make SFMs suitable to large-scale problems. Extensive experiments on real-world datasets demonstrate that the proposed SFMs outperform several state-of-the-art methods in terms of prediction accuracy and computational cost.Comment: 10 page

Improving The Performance of Inventory Control – Taking W Company as an Example

The W company is facing a problem that their demand is intermittent. Because intermittent demand is difficult to predict, there are some models being created to deal with it. Using these models, such as Bootstrapping, Croston’s method, and Discreteauto-regressive-moving-average model, to predict and compare with the current one if any of them outperforms

A Global Method for a Two-Dimensional Cutting Stock Problem in the Manufacturing Industry

A two-dimensional cutting stock problem (2DCSP) needs to cut a set of given rectangular items from standard-sized rectangular materials with the objective of minimizing the number of materials used. This problem frequently arises in different manufacturing industries such as glass, wood, paper, plastic, etc. However, the current literatures lack a deterministic method for solving the 2DCSP. However, this study proposes a global method to solve the 2DCSP. It aims to reduce the number of binary variables for the proposed model to speed up the solving time and obtain the optimal solution. Our experiments demonstrate that the proposed method is superior to current reference methods for solving the 2DCSP

THE EFFECT OF REGULA EXERCISE FOR FUNTIONAL HEALTH OF THE ELDERLY

The purpose of this study was to investigate the performance difference in walking, stair descent and ascent, sit-to-stand, and stand-to-sit, between elderlies who exercise regularly and those who don’t. Twenty elderlies participated in this study (8 males and 12 females). All tests were assessed using a 10-camera Vicon system. The visual3D software was used to analyse data. A positive correlation exists between movement time of stair descent and anterior-posterior balance ability. The negative correlations exist between movement time of stair descent and ascent and balance ability in lateral-medial. A significant difference in balance ability of stair decent exists between those with regular exercise and those without. According to the ACSM principle, regular exercise can indeed reduce the chance of falling in the elderly