منابع مشابه
Efficient Learning of Trajectory Preferences Using Combined Ratings and Rankings
In this paper we propose an approach for modeling and learning human preferences using a combination of absolute (querying an expert for a numerical value) and relative (asking the expert to select the highest-value option from a set) queries. Our approach uses a Gaussian process regression model with an associated likelihood function that can take into account both pairwise preferences and num...
متن کاملClass attendance and students' evaluations of teaching: do no-shows bias course ratings and rankings?
BACKGROUND Many university departments use students' evaluations of teaching (SET) to compare and rank courses. However, absenteeism from class is often nonrandom and, therefore, SET for different courses might not be comparable. OBJECTIVE The present study aims to answer two questions. Are SET positively biased due to absenteeism? Do procedures, which adjust for absenteeism, change course ra...
متن کاملCorrelating Topic Rankings and Person Rankings to Find Experts
Expert search is about finding people rather than documents. The goal is to retrieve a ranked list of candidates with expertise on a given topic. The task is studied in the context of the enterprise track. We describe an approach that compares topic profiles and candidate profiles directly. These profiles are not based on unordered sets of documents, but on ranked lists. This allows us to diffe...
متن کاملProportional Rankings
In this paper we extend the principle of proportional representation to rankings. We consider the setting where alternatives need to be ranked based on approval preferences. In this setting, proportional representation requires that cohesive groups of voters are represented proportionally in each initial segment of the ranking. Proportional rankings are desirable in situations where initial seg...
متن کاملCollaborative Rankings
In this paper we introduce a new ranking algorithm, called Collaborative Judgement (CJ), that takes into account peer opinions of agents and/or humans on objects (e.g. products, exams, papers) as well as peer judgements over those opinions. The combination of these two types of information has not been studied in previous work in order to produce object rankings. Here we apply Collaborative Jud...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Perinatal Education
سال: 2010
ISSN: 1058-1243
DOI: 10.1624/105812410x530857