This paper presents a novel approach for extracting high-quality pairs as chat knowledge from online discussion forums so as to efficiently support the construction of a chatbot for a certain domain. Given a forum, the high-quality pairs are extracted using a cascaded framework. First, the replies logically relevant to the thread title of the root mes...

We scrutinize and compare, from the perspective of modern theory of social choice, two rules that have been used to rank competitors in Figure Skating for the past decades. The first rule has been in use at least from 1982 until 1998, when it was replaced by a new one. We also compare these two rules with the Borda and the Kemeny rules. The four rules are illustrated with examples and with the ...

We propose an approach for automatically ranking structured documents applied to patent prior art search. Our model, SVM Patent Ranking (SVMPR) incorporates margin constraints that directly capture the specificities of patent citation ranking. Our approach combines patent domain knowledge features with meta-score features from several different general Information Retrieval methods. The trainin...

This paper introduces two new methods for label ranking based on a probabilistic model of ranking data, called the Plackett-Luce model. The idea of the first method is to use the PL model to fit locally constant probability models in the context of instance-based learning. As opposed to this, the second method estimates a global model in which the PL parameters are represented as functions of t...

This paper proposes a human age estimation method using Ranking SVM method. Given a face image, most previous methods estimate the human age directly. However, the face images from the same age vary so much that it’s really a difficult problem to estimate the human age accurately. In this work, we adopt an alternative way to estimate the human age. First, the rank relationship of the ages is le...

This paper presents our method to retrieve relevant queries given a new question in the context of Discovery Challenge: Learning to Re-Ranking Questions for Community Question Answering competition. In order to do that, a set of learning to rank methods was investigated to select an appropriate method. The selected method was optimized on training data by using a search strategy. After optimizi...

In this paper, a preference aggregation method is developed for ranking alternative courses of actions by combining preference rankings of alternatives given on individual criteria or by individual decision makers. In the method, preference rankings are viewed as constraints on alternative utilities, which are normalized, and linear programming models are constructed to estimate utility interva...