Term weighting for document ranking and retrieval has been an important research topic in information retrieval for decades. We propose a novel term weighting method based on a hypothesis that a term’s role in accumulated retrieval sessions in the past affects its general importance regardless. It utilizes availability of past retrieval results consisting of the queries that contain a particula...

The development of new schemes for weighting DNA sequence data for phylogenetic analysis continues to outpace the development of consensus on the most appropriate weights. The present study is an exploration of the similarities and differences between results from 22 character weighting schemes when applied to a study of barbet and toucan (traditional avian families Capitonidae and Ramphastidae...

We propose a simple and straightforward way of creating powerful image representations via cross-dimensional weighting and aggregation of deep convolutional neural network layer outputs. We first present a generalized framework that encompasses a broad family of approaches and includes cross-dimensional pooling and weighting steps. We then propose specific non-parametric schemes for both spatia...

In this paper we compare the performance of three constraint weighting schemes with one of the latest and fastest WSAT heuristics: rnovelty. We extend previous results from satisfiability testing by looking at the broader domain of constraint satisfaction and test for differences in performance using randomly generated problems and problems based on realistic situations and assumptions. We find...

A simple weighting scheme for atomic refinement is discussed. The approach, called 'Bayesian weighting', is designed to be robust with respect to the bias that arises from the incomplete nature of the atomic model, which in macromolecular crystallography is typically quite serious. Bayesian weights are based on the mean-squared residual errors over shells of resolution, with centric and acentri...

Using separate indices for each element and merging their results has proven to be a feasible way of performing XML element retrieval; however, there has been little work on evaluating how the main method parameters affect the results. We study the effect of using different weighting models for computing rankings at the single index level and using different merging techniques for combining suc...

The work described here initially formed part of a triangulation exercise to establish the effectiveness of the Query Term Order algorithm. The methodology produced subsequently proved to be a reliable indicator of quality for summarising English web documents. We utilised the human summaries from the Document Understanding Conference data, and generated queries automatically for testing the QT...

Supervised term weighting could improve the performance of text categorization. A way proven to be effective is to give more weight to terms with more imbalanced distributions across categories. This paper shows that supervised term weighting should not just assign large weights to imbalanced terms, but should also control the trade-off between over-weighting and under-weighting. Overweighting,...

Approaches for solving the timing-driven placement problem have traditionally been either net-based or path-based; see, e.g., [7] for an overview. Net weighting methods, which fall in the latter category, have been a popular tool in analytical placers [16, 8, 9] for handling timing-driven placement. They enjoy a number of advantages, including very low computational complexity, high flexibility...

A multi-objective forest management process employing mathematical programming and the analytic hierarchy process has been developed for systematically incorporating public input. The process was tested as a ―proof of concept‖ for four values and five stakeholders in Crown License 5 in New Brunswick. The impacts of tradeoffs among various weighting schemes were evaluated. Analyses of stakeholde...