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学者姓名：姚一豫
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| GB/T 7714 | Zhong, Ning , Liu, Jiming , Shi, Yong et al. An interview with Professor Raj Reddy on Web Intelligence (WI) and Computational Social Science (CSS) [J]. | Web Intelligence , 2018 , 16 (3) : 143-146 . |
| MLA | Zhong, Ning et al. "An interview with Professor Raj Reddy on Web Intelligence (WI) and Computational Social Science (CSS)" . | Web Intelligence 16 . 3 (2018) : 143-146 . |
| APA | Zhong, Ning , Liu, Jiming , Shi, Yong , Yao, Yiyu . An interview with Professor Raj Reddy on Web Intelligence (WI) and Computational Social Science (CSS) . | Web Intelligence , 2018 , 16 (3) , 143-146 . |
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Abstract ：
Recommender systems aim to identify items that a user may like. In this paper, we discuss a three-way decision approach which provides a more meaningful way to recommend items to a user. Besides recommended items and not recommended items, the proposed model adds a set of items that are possibly recommended to users. In the model, we focus on two issues. One is the computation of required thresholds to define the three sets based on the decision-theoretic rough set model. The other is the notion of user preference on the three sets which forms the basis of a ranking strategy, and then a pair-wise preference learning algorithm using gradient descent is adopted for inferring latent vectors for users and items. Working with a sigmoid function of a product of a user and item latent vector, we estimate the probability that the user prefers the item to make recommendations. Experimental results show that the proposed method improves recommendation quality from the cost-sensitive view. (C) 2017 Elsevier Inc. All rights reserved.
Keyword ：
Three-way decision Three-way decision Recommender system Recommender system
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| GB/T 7714 | Huang, Jiajin , Wang, Jian , Yao, Yiyu et al. Cost-sensitive three-way recommendations by learning pair-wise preferences [J]. | INTERNATIONAL JOURNAL OF APPROXIMATE REASONING , 2017 , 86 : 28-40 . |
| MLA | Huang, Jiajin et al. "Cost-sensitive three-way recommendations by learning pair-wise preferences" . | INTERNATIONAL JOURNAL OF APPROXIMATE REASONING 86 (2017) : 28-40 . |
| APA | Huang, Jiajin , Wang, Jian , Yao, Yiyu , Zhong, Ning . Cost-sensitive three-way recommendations by learning pair-wise preferences . | INTERNATIONAL JOURNAL OF APPROXIMATE REASONING , 2017 , 86 , 28-40 . |
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Abstract ：
A recommender system aims at recommending items that users might be interested in. With an increasing popularity of social tagging systems, it becomes urgent to model recommendations on users, items, and tags in a unified way. In this paper, we propose a framework for studying recommender systems by modeling user preferences as a relation on (user, item, tag) triples. We discuss tag-aware recommender systems from two aspects. On the one hand, we compute associations between users and items related to tags by using an adaptive method and recommend tags to users or predict item properties for users. On the other hand, by taking the similarity-based recommendation as a case study, we discuss similarity measures from both qualitative and quantitative perspectives and k-nearest neighbors and reverse k-nearest neighbors for recommendations.
Keyword ：
Tag Tag recommender system recommender system preference relation preference relation
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| GB/T 7714 | Hunag, Jiajin , Yuan, Xi , Zhong, Ning et al. Modeling Tag-Aware Recommendations Based on User Preferences [J]. | INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING , 2015 , 14 (5) : 947-970 . |
| MLA | Hunag, Jiajin et al. "Modeling Tag-Aware Recommendations Based on User Preferences" . | INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING 14 . 5 (2015) : 947-970 . |
| APA | Hunag, Jiajin , Yuan, Xi , Zhong, Ning , Yao, Yiyu . Modeling Tag-Aware Recommendations Based on User Preferences . | INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING , 2015 , 14 (5) , 947-970 . |
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Abstract ：
One of the fundamental tasks of targeted marketing is to elicit associations between customers and products. Based on the results from information retrieval and utility theory, this article proposes a unified framework of targeted marketing. The customer judgments of products are formally described by preference relations and the connections of customers and products are quantitatively measured by market value functions. Two marketing strategies, known as the customer-oriented and product-oriented marketing strategies, are investigated. Four marketing models are introduced and examined. They represent, respectively, the relationships between a group of customers and a group of products, between a group of customers and a single product, between a single customer and a group of products, and between a single customer and a single product. Linear and bilinear market value functions are suggested and studied. The required parameters of a market value function can be estimated by exploring three types of information, namely, customer profiles, product profiles, and transaction data. Experiments on a real-world data set are performed to demonstrate the effectiveness of the proposed framework.
Keyword ：
targeted marketing targeted marketing utility theory utility theory Web intelligence Web intelligence customer preference customer preference
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| GB/T 7714 | Huang, Jiajin , Zhong, Ning , Yao, Yiyu . A UNIFIED FRAMEWORK OF TARGETED MARKETING USING CUSTOMER PREFERENCES [J]. | COMPUTATIONAL INTELLIGENCE , 2014 , 30 (3) : 451-472 . |
| MLA | Huang, Jiajin et al. "A UNIFIED FRAMEWORK OF TARGETED MARKETING USING CUSTOMER PREFERENCES" . | COMPUTATIONAL INTELLIGENCE 30 . 3 (2014) : 451-472 . |
| APA | Huang, Jiajin , Zhong, Ning , Yao, Yiyu . A UNIFIED FRAMEWORK OF TARGETED MARKETING USING CUSTOMER PREFERENCES . | COMPUTATIONAL INTELLIGENCE , 2014 , 30 (3) , 451-472 . |
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| GB/T 7714 | Chen, Jianhui , Ma, Jianhua , Zhong, Ning et al. WaaS: Wisdom as a Service [J]. | IEEE INTELLIGENT SYSTEMS , 2014 , 29 (6) : 40-47 . |
| MLA | Chen, Jianhui et al. "WaaS: Wisdom as a Service" . | IEEE INTELLIGENT SYSTEMS 29 . 6 (2014) : 40-47 . |
| APA | Chen, Jianhui , Ma, Jianhua , Zhong, Ning , Yao, Yiyu , Liu, Jiming , Huang, Runhe et al. WaaS: Wisdom as a Service . | IEEE INTELLIGENT SYSTEMS , 2014 , 29 (6) , 40-47 . |
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Abstract ：
The rapid development of the Internet and the Internet of Things accelerates the emergence of the hyper world. It has become a pressing research issue to realize the organic amalgamation and harmonious symbiosis among humans, computers, and things in the hyper world, which consists of the social world, the physical world, and the information world (cyber world). In this paper, the notion of Wisdom Web of Things (W2T) is proposed in order to address this issue. As inspired by the material cycle in the physical world, the W2T focuses on the data cycle, namely "from things to data, information, knowledge, wisdom, services, humans, and then back to things." A W2T data cycle system is designed to implement such a cycle, which is, technologically speaking, a practical way to realize the harmonious symbiosis of humans, computers, and things in the emerging hyper world.
Keyword ：
Transparent service Transparent service Internet of Things Internet of Things Data cycle Data cycle Wisdom Web of Things Wisdom Web of Things Active service Active service
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| GB/T 7714 | Zhong, Ning , Ma, Jian Hua , Huang, Run He et al. Research challenges and perspectives on Wisdom Web of Things (W2T) [J]. | JOURNAL OF SUPERCOMPUTING , 2013 , 64 (3) : 862-882 . |
| MLA | Zhong, Ning et al. "Research challenges and perspectives on Wisdom Web of Things (W2T)" . | JOURNAL OF SUPERCOMPUTING 64 . 3 (2013) : 862-882 . |
| APA | Zhong, Ning , Ma, Jian Hua , Huang, Run He , Liu, Ji Ming , Yao, Yiyu , Zhang, Yao Xue et al. Research challenges and perspectives on Wisdom Web of Things (W2T) . | JOURNAL OF SUPERCOMPUTING , 2013 , 64 (3) , 862-882 . |
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Abstract ：
Peculiarity oriented mining (POM), aimed at discovering peculiarity rules hidden in a dataset, is a data mining method. Peculiarity factor (PF) is one of the most important concepts in POM. In this paper, it is proved that PF can accurately characterize the peculiarity of data sampled from a normal distribution. However, for a general one-dimensional distribution, it does not have the property. A local version of PF, called LPF, is proposed to solve the difficulty. LPF can effectively describe the peculiarity of data sampled from a continuous one-dimensional distribution. Based on LPF, a framework of local peculiarity oriented mining is presented, which consists of two steps, namely, peculiar data identification and peculiar data analysis. Two algorithms for peculiar data identification and a case study of peculiar data analysis are given to make the framework practical. Experiments on several benchmark datasets show their good performance.
Keyword ：
local peculiarity oriented mining local peculiarity oriented mining peculiarity factor peculiarity factor Data mining Data mining local peculiarity factor local peculiarity factor outlier detection outlier detection
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| GB/T 7714 | Yang, Jian , Zhong, Ning , Yao, Yiyu et al. LOCAL PECULIARITY ORIENTED DATA MINING AND ITS APPLICATION IN OUTLIER DETECTION [J]. | INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING , 2012 , 11 (6) : 1155-1181 . |
| MLA | Yang, Jian et al. "LOCAL PECULIARITY ORIENTED DATA MINING AND ITS APPLICATION IN OUTLIER DETECTION" . | INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING 11 . 6 (2012) : 1155-1181 . |
| APA | Yang, Jian , Zhong, Ning , Yao, Yiyu , Wang, Jue . LOCAL PECULIARITY ORIENTED DATA MINING AND ITS APPLICATION IN OUTLIER DETECTION . | INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING , 2012 , 11 (6) , 1155-1181 . |
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Abstract ：
To investigate the role of lateral inferior prefrontal cortex (LIPFC) during information retrieval, we used two tasks based on the phenomenon of basic-level advantage and its reversal to examine the activities in this region across tasks. As expected, this region was involved in both tasks during the processing of information retrieval. ROI analysis showed there was a stronger activation in word-picture matching (WP) task in LIPFC than that in picture-word matching (PW) task. Moreover, although as for the behavioral performance, we observed a typical basic-level advantage effect in PW task and the reversal advantage effect to more general level in WP task, the activities in left LIPFC were similar across the tasks, which was not consistent with our expectation. The intensity was weakest in the condition of intermediate level, and the differences between intermediate and other two levels reached significant level in WP task. These results suggested the region of LIPFC controlled retrieval of knowledge information, and the activation in LIPFC depended more on internal memory system, not the external task demand. © 2011 Springer-Verlag.
Keyword ：
Information retrieval Information retrieval Activation analysis Activation analysis Search engines Search engines Chemical activation Chemical activation
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| GB/T 7714 | Zhou, Haiyan , Liu, Jieyu , Jing, Wei et al. The role of lateral inferior prefrontal cortex during information retrieval [C] . 2011 : 53-63 . |
| MLA | Zhou, Haiyan et al. "The role of lateral inferior prefrontal cortex during information retrieval" . (2011) : 53-63 . |
| APA | Zhou, Haiyan , Liu, Jieyu , Jing, Wei , Qin, Yulin , Lu, Shengfu , Yao, Yiyu et al. The role of lateral inferior prefrontal cortex during information retrieval . (2011) : 53-63 . |
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Abstract ：
Under the context of large-scale scientific literatures, this paper provides a user-centric approach for refining and processing incomplete or vague query based on cognitive- and granularity-based strategies. From the viewpoints of user interests retention and granular information processing, we examine various strategies for user-centric unification of search and reasoning. Inspired by the basic level for human problem-solving in cognitive science, we refine a query based on retained user interests. We bring the multi-level, multi-perspective strategies from human problem-solving to large-scale search and reasoning. The power/exponential law-based interests retention modeling, network statistics-based data selection, and ontology-supervised hierarchical reasoning are developed to implement these strategies. As an illustration, we investigate some case studies based on a large-scale scientific literature dataset, DBLP. The experimental results show that the proposed strategies are potentially effective.
Keyword ：
User interests retention User interests retention Multiple perspectives Multiple perspectives Unifying search and reasoning Unifying search and reasoning Granularity Granularity Multi-level specificity Multi-level specificity Multi-level completeness Multi-level completeness Starting point Starting point
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| GB/T 7714 | Zeng, Yi , Zhong, Ning , Wang, Yan et al. User-centric query refinement and processing using granularity-based strategies [J]. | KNOWLEDGE AND INFORMATION SYSTEMS , 2011 , 27 (3) : 419-450 . |
| MLA | Zeng, Yi et al. "User-centric query refinement and processing using granularity-based strategies" . | KNOWLEDGE AND INFORMATION SYSTEMS 27 . 3 (2011) : 419-450 . |
| APA | Zeng, Yi , Zhong, Ning , Wang, Yan , Qin, Yulin , Huang, Zhisheng , Zhou, Haiyan et al. User-centric query refinement and processing using granularity-based strategies . | KNOWLEDGE AND INFORMATION SYSTEMS , 2011 , 27 (3) , 419-450 . |
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Peculiarity-oriented mining is a data mining method consisting of peculiar data identification and peculiar data analysis. Peculiarity factor and local peculiarity factor are important concepts employed to describe the peculiarity of a data point in the identification step. One can study the notions at both attribute and record levels. In this paper, a new record LPF called distance-based record LPF (D-record LPF) is proposed, which is defined as the sum of distances between a point and its nearest neighbors. The authors prove that D-record LPF can characterize the probability density of a continuous m-dimensional distribution accurately. This provides a theoretical basis for some existing distance-based anomaly detection techniques. More importantly, it also provides an effective method for describing the class-conditional probabilities in a Bayesian classifier. The result enables us to apply D-record LPF to solve classification problems. A novel algorithm called LPF-Bayes classifier and its kernelized implementation are proposed, which have some connection to the Bayesian classifier. Experimental results on several benchmark datasets demonstrate that the proposed classifiers are competitive to some excellent classifiers such as AdaBoost, support vector machines and kernel Fisher discriminant.
Keyword ：
Local peculiarity factor Local peculiarity factor LPF-Bayes classifier LPF-Bayes classifier Peculiarity factor Peculiarity factor Peculiarity analysis Peculiarity analysis Bayesian classifier Bayesian classifier
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| GB/T 7714 | Yang, Jian , Zhong, Ning , Yao, Yiyu et al. Record-level peculiarity-based data analysis and classifications [J]. | KNOWLEDGE AND INFORMATION SYSTEMS , 2011 , 28 (1) : 149-173 . |
| MLA | Yang, Jian et al. "Record-level peculiarity-based data analysis and classifications" . | KNOWLEDGE AND INFORMATION SYSTEMS 28 . 1 (2011) : 149-173 . |
| APA | Yang, Jian , Zhong, Ning , Yao, Yiyu , Wang, Jue . Record-level peculiarity-based data analysis and classifications . | KNOWLEDGE AND INFORMATION SYSTEMS , 2011 , 28 (1) , 149-173 . |
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