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Among different hybrid recommendation techniques, network-based entity recommendation methods, which utilize user or item relationship information, are beginning to attract increasing attention recently. Most of the previous studies in this category only consider a single relationship type, such as friendships in a social network. In many scenarios, the(More)
Real-world, multiple-typed objects are often interconnected, forming heterogeneous information networks. A major challenge for link-based clustering in such networks is its potential to generate many different results, carrying rather diverse semantic meanings. In order to generate desired clustering, we propose to use <i>meta-path</i>, a path that connects(More)
—A Cyber-Physical System (CPS) integrates physical devices (e.g., sensors, cameras) with cyber (or informational) components to form a situation-integrated analytical system that responds intelligently to dynamic changes of the real-world scenarios. One key issue in CPS research is trustworthiness analysis of the observed data: Due to technology limitations(More)
Nearest neighbor (NN) classifier with dynamic time warping (DTW) is considered to be an effective method for time series classification. The performance of NN-DTW is dependent on the DTW constraints because the NN classifier is sensitive to the used distance function. For time series classification, the global path constraint of DTW is learned for(More)
Due to their commercial value, <i>search engines</i> and <i>recommender systems</i> have become two popular research topics in both industry and academia over the past decade. Although these two fields have been actively and extensively studied separately, researchers are beginning to realize the importance of the scenarios at their intersection: providing(More)
Real-world execution traces record performance problems that are likely perceived at deployment sites. However, those problems can be rooted subtly and deeply into system layers or other components far from the place where delays are initially observed. To tackle challenges of identifying deeply rooted problems, we propose a new trace-based approach(More)
To reveal information hiding in link space of bibliographical networks, link analysis has been studied from different perspectives in recent years. In this paper, we address a novel problem namely citation prediction, that is: given information about authors, topics, target publication venues as well as time of certain research paper, finding and predicting(More)
Abstr act. The advance of object tracking technologies leads to huge volumes of spatio-temporal data accumulated in the form of location trajectories. Such data bring us new opportunities and challenges in efficient trajectory retrieval. In this paper, we study a new type of query that finds the k Nearest Neighboring Trajectories (k-NNT) with the minimum(More)
Recent studies suggest that by using additional user or item relationship information when building hybrid recommender systems, the recommendation quality can be largely improved. However, most such studies only consider a single type of relationship, e.g., social network. Notice that in many applications, the recommendation problem exists in an(More)
— We present a review of the various integer linear programming (ILP) formulations that have been proposed for the routing and wavelength assignment problem in WDM optical networks with a unified and simplified notation. We consider both symmetrical and asymmetrical traffic matrices. We propose a new formulation for symmetrical traffic. We show that all(More)