Machine Learning in Automated Text Categorization

The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last ten years, due to the increased availability of documents in digital form and the ensuing need to organize them. In the research community the dominant approach to this problem is based on machine learning techniques: a general inductive process automatically builds a classifier by learning, from a set of preclassified documents, the characteristics of the categories. The advantages of this approach over the knowledge engineering approach (consisting in the manual definition of a classifier by domain experts) are a very good effectiveness, considerable savings in terms of expert manpower, and straightforward portability to different domains. This survey discusses the main approaches to text categorization that fall within the machine learning paradigm. We will discuss in detail issues pertaining to three different problems, namely document representation, classifier construction, and classifier evaluation.Comment: Accepted for publication on ACM Computing Survey

Soluble forms of tau are toxic in Alzheimer's disease

Accumulation of neurofibrillary tangles (NFT), intracellular inclusions of fibrillar forms of tau, is a hallmark of Alzheimer Disease. NFT have been considered causative of neuronal death, however, recent evidence challenges this idea. Other species of tau, such as soluble misfolded, hyperphosphorylated, and mislocalized forms, are now being implicated as toxic. Here we review the data supporting soluble tau as toxic to neurons and synapses in the brain and the implications of these data for development of therapeutic strategies for Alzheimer’s disease and other tauopathies

Hotel management contracts and deficiencies in owner-operator capital expenditure goal congruency

A review of the findings of prior empirical research concerning hotel management contracts between owners and operators is undertaken. It is noted that management contracts have become increasingly commonplace in the international hotel sector and that gross revenue and gross operating profit are the most extensively used determinants of operator incentive fee remuneration. These findings present a platform for examining how revenue and gross operating profit are deficient in promoting owner-operator goal congruency. In light of this, return on investment (ROI) and residual income (RI) are examined as potential alternative determinants of operator reimbursement. Although it is appears that both ROI and RI as determinants of hotel operator fees would represent an advance in promoting owner-operator goal congruency, a rationale outlining how RI is preferable to ROI is outlined. © 2010 International Council on Hotel, Restaurant and Institutional Education