Abstract of Re-engineering of Industrial CMMI Through this research, I have established a general strategy to appraise an organization against a scale of five process maturity levels whilst maintaining a strong mechanics of CMMI. Reengineering of industrial CMMI proposes a novel method for Industrial Competence ranking of those organizations/companies which are targeting various CMM...

this paper will investigate the optimum portfolio for an investor, taking into account 5 criteria. the mean variance model of portfolio optimization that was introduced by markowitz includes two objective functions; these two criteria, risk and return do not encompass all of the information about investment; information like annual dividends, s&p star ranking and return in later years which...

This paper studies global ranking problem by learning to rank methods. Conventional learning to rank methods are usually designed for ‘local ranking’, in the sense that the ranking model is defined on a single object, for example, a document in information retrieval. For many applications, this is a very loose approximation. Relations always exist between objects and it is better to define the ...

Using Lexical and Compositional Semantics to Improve HPSG Parse Selection Chair of the Supervisory Committee: Dr. Emily Bender University of Washington Accurate parse ranking is essential for deep linguistic processing applications and is one of the classic problems for academic research in NLP. Despite significant advances, there remains a big need for improvement, especially for domains where...

In 1929, Zermelo proposed a probabilistic model for ranking by paired comparisons and showed that this model produces a unique ranking of the objects under consideration when the outcome matrix is irreducible. When the matrix is reducible, the model may yield only a partial ordering of the objects. In this paper, we analyze a natural extension of Zermelo’s model resulting from a singular pertur...

This research examines whether a low-ranking member in a high-status category (e.g., a low-end model of a high-end brand) or a high-ranking member in a low-status category (e.g., a high-end model of a low-end brand) is favored, holding the objective qualities of the items constant. Brand equity research suggests that the quality of a brand is more important than the ranking of a product within ...

The problem of ranking arises ubiquitously in almost every aspect of life, and in particular in Machine Learning/Information Retrieval. A statistical model for ranking predicts how humans rank subsets V of some universe U . In this work we define a statistical model for ranking that satisfies certain desirable properties. The model automatically gives rise to a logistic regression based approac...

The problem of ranking arises ubiquitously in almost every aspect of life, and in particular in Machine Learning/Information Retrieval. A statistical model for ranking predicts how humans rank subsets V of some universe U . In this work we define a statistical model for ranking that satisfies certain desirable properties. The model automatically gives rise to a logistic regression based approac...

T research examines whether a low-ranking member in a high-status category (e.g., a low-end model of a high-end brand) or a high-ranking member in a low-status category (e.g., a high-end model of a low-end brand) is favored, holding the objective qualities of the items constant. Brand equity research suggests that the quality of a brand is more important than the ranking of a product within a b...