DocTag2Vec: An Embedding Based Multi-label Learning Approach for Document Tagging

Tagging news articles or blog posts with relevant tags from a collection of predefined ones is coined as document tagging in this work. Accurate tagging of articles can benefit several downstream applications such as recommendation and search. In this work, we propose a novel yet simple approach called DocTag2Vec to accomplish this task. We substantially extend Word2Vec and Doc2Vec---two popular models for learning distributed representation of words and documents. In DocTag2Vec, we simultaneously learn the representation of words, documents, and tags in a joint vector space during training, and employ the simple $k$-nearest neighbor search to predict tags for unseen documents. In contrast to previous multi-label learning methods, DocTag2Vec directly deals with raw text instead of provided feature vector, and in addition, enjoys advantages like the learning of tag representation, and the ability of handling newly created tags. To demonstrate the effectiveness of our approach, we conduct experiments on several datasets and show promising results against state-of-the-art methods.Comment: 10 page

Why do undergraduate marketing majors select marketing as a business major? Evidence from Australasia

This research examines the reasons behind marketing majors’ decision to select marketing as a major, where students have the option to select more than one major toward their undergraduate degree. Results of surveys conducted at two universities, one in Australia and one in New Zealand, provide some new findings as well as extending findings from earlier studies. This research complements existing studies on the topic by providing empirical evidence from Australasia. The results also suggest that marketing is the most popular first-choice major for Australasian marketing majors

METCAN: The metal matrix composite analyzer

Metal matrix composites (MMC) are the subject of intensive study and are receiving serious consideration for critical structural applications in advanced aerospace systems. MMC structural analysis and design methodologies are studied. Predicting the mechanical and thermal behavior and the structural response of components fabricated from MMC requires the use of a variety of mathematical models. These models relate stresses to applied forces, stress intensities at the tips of cracks to nominal stresses, buckling resistance to applied force, or vibration response to excitation forces. The extensive research in computational mechanics methods for predicting the nonlinear behavior of MMC are described. This research has culminated in the development of the METCAN (METal Matrix Composite ANalyzer) computer code

Finite element substructuring methods for composite mechanics

Finite element substructuring strategies are presented to obtain numerical solutions for three typical problems of interest to the composites community: (1) impact and toughness characterization of composites using Charpy's impact test specimen; (2) free-edge stress analysis of composite laminates; and (3) fracture toughness predictions of composites for individual and combined fracture of modes I, II, and III. The key issue common to these problems is the presence of singular or near singular stress fields. The regions prone to see steep stress gradients are substructured with progressively refined meshes to study the local response simultaneously with the global response. The results from the select examples indicate that finite element substructuring methods are computationally effective for composite singularity mechanics

Design Procedures for Fiber Composite Box Beams

Step-by-step procedures are described which can be used for the preliminary design of fiber composite box beams subjected to combined loadings. These procedures include a collection of approximate closed-form equations so that all the required calculations can be performed using pocket calculators. Included is an illustrated example of a tapered cantilever box beam subjected to combined loads. The box beam is designed to satisfy strength, displacement, buckling, and frequency requirements

Computational simulation of high temperature metal matrix composite behavior

Computational procedures are described to simulate the thermal and mechanical behavior of high temperature metal matrix composite (HT MMC) in the following four broad areas: (1) behavior of HT MMC from micromechanics to laminate; (2) HT MMC structural response for simple and complex structural components; (3) HT MMC microfracture; and (4) tailoring of HT MMC behavior for optimum specific performance. Representative results from each area are presented to illustrate the effectiveness of the computational simulation procedures. Relevant reports are referenced for extended discussion regarding the specific area

Using Wikipedia for Hierarchical Finer Categorization of Named Entities

PACLIC 23 / City University of Hong Kong / 3-5 December 200

The three faces of inter-organizational relationships: towards a theory of logistics relationships, strategy, and inter-organizational learning

A growing concern of today\u27s business executives is the increasing volatility of their organization\u27s environment. In order to manage these turbulent environments, inter-firm collaborations are becoming more and more pervasive. A critical question, however, is are such inter-organizational relationships working? According to several researchers they are apparently not very successful. The purpose of this research is to develop a rigorous, comprehensive, wellgrounded theoretical model describing inter-organizational logistics relationships (lOLRs). It began with the following research questions in mind: How do lOLRs form? How do strategic and non-strategic lOLRs differ? Finally, is the learning perspective more effective than existing ones, in describing and explaining lOLRs? To find answers to these questions, more than 40 logistics professionals, at various levels - ranging from Directors to Managers and Supervisors - in 8 organizations were interviewed and their responses were recorded, transcribed and carefully analyzed. Following an extremely rigorous analysis, involving one - at times two - other colleague(s) three dimensions were identified: (1) Designed - Evolutionary dimension (based on the nature of lOLR formation); (2) Operational - Strategic dimension (based on the of criticality of the lOLR); (3) Individual - Organizational dimension (reflecting the level of involvement). In doing so, characteristics of lOLRs which emerged from the study were identified. Thus on Face One , which was formed between the Designed - Evolutionary and Operational - Strategic dimensions, a typology of lOLR formation, was developed. This typology is shown to have its roots in Mintzberg\u27s (1978) typology of strategies; sharing many of the characteristics therein. A 3x3 matrix, forms Face Two of the Three Face model. \u27Occupants\u27 to six of the nine cells (Cells 1,2,3,5,6, and 9) were identified while three others (Cells 4,7, and 8) were found to be empty. A careful review of cell-features clearly supports the lack of \u27occupants\u27; transaction costs of managing and monitoring lOLRs in these cells is too high to warrant their existence. Bringing the two Faces together automatically resulted in Face Three , which was formed between the Designed - Evolutionary and Individual - Organizational dimensions. Learning characteristics of the lOLRs identified in the study were found identical to those identified by earlier researchers such as Shrivastava (1983) and DiBella et al. (1996). Finally, based on the characteristics of the lOLRs identified through this research, several propositions for future research are presented