2013 IEEE 25th International Conference on Tools with Artificial Intelligence最新文献

ICAMF: Improved Context-Aware Matrix Factorization for Collaborative Filtering 改进的上下文感知矩阵分解协同过滤

2013 IEEE 25th International Conference on Tools with Artificial Intelligence Pub Date : 2013-11-04 DOI: 10.1109/ICTAI.2013.20

Jiyun Li, Pengcheng Feng, Juntao Lv

引用次数: 12

An Algorithm for Mining Top K Influential Community Based Evolutionary Outliers in Temporal Dataset 基于时间数据集Top K影响群体的进化离群点挖掘算法

2013 IEEE 25th International Conference on Tools with Artificial Intelligence Pub Date : 2013-11-04 DOI: 10.1109/ICTAI.2013.84

Yun Hu, Junyuan Xie, Chong-Jun Wang, Zuojian Zhou

{"title":"An Algorithm for Mining Top K Influential Community Based Evolutionary Outliers in Temporal Dataset","authors":"Yun Hu, Junyuan Xie, Chong-Jun Wang, Zuojian Zhou","doi":"10.1109/ICTAI.2013.84","DOIUrl":"https://doi.org/10.1109/ICTAI.2013.84","url":null,"abstract":"Identifying outlier objects against main community evolution trends is not only meaningful itself for the purpose of finding novel evolution behaviors, but also helpful for better understanding the mainstream of community evolution. With the definition of community belongingness matrix of data objects, we constructed the transition matrix to least square optimize the pattern of evolutionary quantity between two consecutive belongingness snapshots. A set of properties about the transition matrix is discussed, which reveals its close relation to the step by step community membership change. The transition matrix is further optimized using robust regression methods by minimizing the disturbance incurred by the outliers, and the outlier factor of the anomalous object was defined. Being aware that large proportion of trivial but nomadic objects may exist in large datasets. This paper focus only on the influential community evolutionary outliers which both show remarkable difference from the main body of their community and sharp changes of their membership role within the communities. An algorithm on detection such kind of outliers are purposed in the paper. Experimental results on both synthetic and real world datasets show that the proposed approach is highly effective and efficient in discovering reasonable influential evolutionary community outliers.","PeriodicalId":140309,"journal":{"name":"2013 IEEE 25th International Conference on Tools with Artificial Intelligence","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114656287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Learning Occupancy in Single Person Offices with Mixtures of Multi-lag Markov Chains 多滞后马尔可夫链混合下的单人办公室学习占用

2013 IEEE 25th International Conference on Tools with Artificial Intelligence Pub Date : 2013-11-04 DOI: 10.1109/ICTAI.2013.32

C. Manna, D. Fay, Kenneth N. Brown, Nic Wilson

引用次数: 17

Declarative Heuristics in Constraint Satisfaction 约束满足中的陈述启发式

2013 IEEE 25th International Conference on Tools with Artificial Intelligence Pub Date : 2013-11-04 DOI: 10.1109/ICTAI.2013.150

E. Teppan, G. Friedrich

{"title":"Declarative Heuristics in Constraint Satisfaction","authors":"E. Teppan, G. Friedrich","doi":"10.1109/ICTAI.2013.150","DOIUrl":"https://doi.org/10.1109/ICTAI.2013.150","url":null,"abstract":"Constraint Satisfaction Problems (CSPs) have the big advantage of a succinct, declarative and easy to understand representation form. Unfortunately, solving CSPs is NP-complete in the general case. In order to cope with this, common CSP frameworks offer the possibility to use different built-in heuristics. However, the provided built-in heuristics are often not suitable to significantly boost solution calculation. Also the facilities for expressing domain-specific heuristics in a declarative manner within the CSP framework are typically very limited (e.g. by defining a static variable selection order)and thus are often not applicable. As a consequence such domain-specific heuristics are often implemented by means of custom propagators or custom constraints (e.g. a special constraint for bin packing problems) forcing domain experts and knowledge engineers to leave the declarative world and implement the heuristics in a procedural manner. In this paper we propose a new declarative language for expressing domain specific heuristics for CSPs which can be easily integrated in every CSP framework. We also describe a prototype implementation within a state-of-the-art CSP solver and present proof of concept results on real world configuration problem instances.","PeriodicalId":140309,"journal":{"name":"2013 IEEE 25th International Conference on Tools with Artificial Intelligence","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124842420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Information Extraction from the Web: An Ontology-Based Method Using Inductive Logic Programming 网络信息抽取:一种基于本体的归纳逻辑编程方法

2013 IEEE 25th International Conference on Tools with Artificial Intelligence Pub Date : 2013-11-04 DOI: 10.1109/ICTAI.2013.114

Rinaldo Lima, B. Espinasse, Hilário Oliveira, Laura Pentagrossa, F. Freitas

引用次数: 7

More Smear-Based Variable Selection Heuristics for NCSPs 更多基于涂片的ncsp变量选择启发式算法

2013 IEEE 25th International Conference on Tools with Artificial Intelligence Pub Date : 2013-11-04 DOI: 10.1109/ICTAI.2013.151

Ignacio Araya, Víctor Reyes, Cristian Oreallana

引用次数: 8

A Versatile Graph-Based Approach to Package Recommendation 一个通用的基于图的包推荐方法

2013 IEEE 25th International Conference on Tools with Artificial Intelligence Pub Date : 2013-11-04 DOI: 10.1109/ICTAI.2013.130

R. Interdonato, Salvatore Romeo, Andrea Tagarelli, G. Karypis

{"title":"A Versatile Graph-Based Approach to Package Recommendation","authors":"R. Interdonato, Salvatore Romeo, Andrea Tagarelli, G. Karypis","doi":"10.1109/ICTAI.2013.130","DOIUrl":"https://doi.org/10.1109/ICTAI.2013.130","url":null,"abstract":"An emerging trend in research on recommender systems is the design of methods capable of recommending packages instead of single items. The problem is challenging due to a variety of critical aspects, including context-based and user-provided constraints for the items constituting a package, but also the high sparsity and limited accessibility of the primary data used to solve the problem. Most existing works on the topic have focused on a specific application domain (e.g., travel package recommendation), thus often providing ad-hoc solutions that cannot be adapted to other domains. By contrast, in this paper we propose a versatile package recommendation approach that is substantially independent of the peculiarities of a particular application domain. A key aspect in our framework is the exploitation of prior knowledge on the content type models of the packages being generated that express what the users expect from the recommendation task. Packages are learned for each package model, while the recommendation stage is accomplished by performing a PageRank-style method personalized w.r.t. the target user's preferences, possibly including a limited budget. Our developed method has been tested on a TripAdvisor dataset and compared with a recently proposed method for learning composite recommendations.","PeriodicalId":140309,"journal":{"name":"2013 IEEE 25th International Conference on Tools with Artificial Intelligence","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122453692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 26

Optimization of Traffic Lights Timing Based on Multiple Neural Networks 基于多神经网络的交通信号灯定时优化

2013 IEEE 25th International Conference on Tools with Artificial Intelligence Pub Date : 2013-11-04 DOI: 10.1109/ICTAI.2013.126

Michel B. W. De Oliveira, A. A. Neto

引用次数: 11

Variable Objective Large Neighborhood Search: A Practical Approach to Solve Over-Constrained Problems 变目标大邻域搜索:一种解决过度约束问题的实用方法

2013 IEEE 25th International Conference on Tools with Artificial Intelligence Pub Date : 2013-11-04 DOI: 10.1109/ICTAI.2013.147

P. Schaus

引用次数: 6

A Reusable Methodology for the Instantiation of Social Recommender Systems 社会推荐系统实例化的可重用方法

2013 IEEE 25th International Conference on Tools with Artificial Intelligence Pub Date : 2013-11-04 DOI: 10.1142/S0218213014600318

L. Sánchez, J. A. Recio-García, B. Díaz-Agudo

引用次数: 7