2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)最新文献_第2页

Deep Belief Networks Oriented Clustering 面向聚类的深度信念网络

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) Pub Date : 2015-11-01 DOI: 10.1109/ISKE.2015.8

Qi Yang, Hongjun Wang, Tianrui Li, Yan Yang

{"title":"Deep Belief Networks Oriented Clustering","authors":"Qi Yang, Hongjun Wang, Tianrui Li, Yan Yang","doi":"10.1109/ISKE.2015.8","DOIUrl":"https://doi.org/10.1109/ISKE.2015.8","url":null,"abstract":"Deep learning has been popular for a few years, and it shows great capability on unsupervised leaning of representation. Deep belief network consists of multi layers of restricted Boltzmann machine(RBM) and a deep auto-encoder, which uses a stack architecture learning feature layer by layer. The learning rule is that one deeper layer learns more complex representations, which are the high level features of the input data, from the representations learnt by the layer before. Fuzzy C-Means(FCM) is one of the most popular clustering algorithms, which allows one piece of data belong to several clusters. In this paper the authors propose a novel clustering model, and introduce a novel clustering technique(DBNOC) which combines deep belief network and fuzzy c-means. The main idea is that: first, it clusters with the high level representations learnt by stacked RBM to produce the initial cluster center, then it uses the fine-tune step including one center holding clustering algorithm and deep auto-encoder to optimize the cluster center and membership between input data and every cluster by cross iteration. The authors use FCM clustering algorithm to fulfill the model and do experiment on both low dimensional datasets and high dimensional datasets. The experiment results suggest that the proposed deep belief network oriented clustering method is better than the standard K-Means and FCM algorithm on the test datasets. Even on high dimensional datasets, the DBNOC clustering method show more generalization. What's more, the proposed model is suitable both in theoretical and practical.","PeriodicalId":312629,"journal":{"name":"2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133412272","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: 3

Heterogeneous Feature Space Based Task Selection Machine for Unsupervised Transfer Learning 基于异构特征空间的无监督迁移学习任务选择机

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) Pub Date : 2015-11-01 DOI: 10.1109/ISKE.2015.29

Shan Xue, Jie Lu, Guangquan Zhang, Li Xiong

引用次数: 2

A Novel FAHP Based Book Recommendation Method by Fusing Apriori Rule Mining 融合Apriori规则挖掘的基于FAHP的图书推荐方法

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) Pub Date : 2015-11-01 DOI: 10.1109/ISKE.2015.44

Yining Teng, Lanshan Zhang, Ye Tian, Xiang Li

{"title":"A Novel FAHP Based Book Recommendation Method by Fusing Apriori Rule Mining","authors":"Yining Teng, Lanshan Zhang, Ye Tian, Xiang Li","doi":"10.1109/ISKE.2015.44","DOIUrl":"https://doi.org/10.1109/ISKE.2015.44","url":null,"abstract":"Book recommendation is becoming increasingly significant library service, considering it improve access to relevant books by making personal suggestions based on previous examples of user's preference. Most existing approaches are either collaborative-filtering based, considering the data sparsity and cold-start problems, collaborative-filtering approaches suffer from many challenges. In this paper, we present a Fuzzy Analytical Hierarchy Process (FAHP) based method by fusing Apriori rule mining. Apparently, multiple factors (e.g., similar preference, professional background, education degree and book's publishing house etc.) may influence reader's borrowing decision. Therefore, we first adopt Apriori algorithm to develop association analysis for evaluating the relevance of books in terms of book-loan history. Second, FAHP takes the result of association between books and other subjective/objective factors into account and makes final recommendation according to an overall ranking result. A thorough experimental comparison, based on real-world data, illustrates advantage of our scheme over collaborative filtering approaches.","PeriodicalId":312629,"journal":{"name":"2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114715285","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: 6

Fuzzy Spectral Partition Ensemble Based on Occasion 基于场合的模糊谱划分集成

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) Pub Date : 2015-11-01 DOI: 10.1109/ISKE.2015.47

Xiaolong Meng, Yan Yang, Hongjun Wang

引用次数: 0

Adaptive Sampling Algorithm with Endocrine Regulation Mechanism for Wireless Sensor Network 无线传感器网络中内分泌调节机制的自适应采样算法

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) Pub Date : 2015-11-01 DOI: 10.1109/ISKE.2015.66

Jiankai Zhang, L. Ren, Yongsheng Ding, K. Hao

引用次数: 3

An Event-Oriented Multi-pass Sieve Module for Coreference Resolution 面向事件的多通道筛选模块

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) Pub Date : 2015-11-01 DOI: 10.1109/ISKE.2015.56

Qiang Li, Zongtian Liu, Lei Chen, Xianchuan Wang

引用次数: 1

Object Recognition Base on Deep Belief Network 基于深度信念网络的目标识别

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) Pub Date : 2015-11-01 DOI: 10.1109/ISKE.2015.60

Yajun Zhang, Zongtian Liu, Wen Zhou, Yalan Zhang

{"title":"Object Recognition Base on Deep Belief Network","authors":"Yajun Zhang, Zongtian Liu, Wen Zhou, Yalan Zhang","doi":"10.1109/ISKE.2015.60","DOIUrl":"https://doi.org/10.1109/ISKE.2015.60","url":null,"abstract":"Event ontology is a general knowledge base constructed by event as the basic knowledge unit for computer communication. Event contains six elements which are action, object, time, environment, assertion and language performance. In this paper, we mainly discuss object elements recognition. There are several mainly existing way to recognize object: methods based on rule, statistical and shallow machine learning. Although these methods can get better recognition results in a particular environment, they have nature defects. For instance, it is difficult for them to do feature extraction and they can not achieve complex function approximation, leading to low recognition accuracy and scalability. Aiming at problems of existing object recognition methods, we present a Chinese emergency object recognition model based on deep learning (CEORM). Firstly, we use word segmentation system (LTP) to segment sentence, and classify words according to annotating elements in CEC2.0 corpus, and then obtain each word's vectorization of multiple features, which include part of speech, dependency grammar, length, location. We obtain word's deep semantic characteristics from the collection after vectorization using deep belief network, finally, object elements are classified and recognized. Extensive testing analysis shows that our proposed method can achieve better recognition effect.","PeriodicalId":312629,"journal":{"name":"2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129172364","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: 2

Foreign Particle Inspection for Infusion Fluids via Robust Dictionary Learning 基于鲁棒字典学习的输液异物检测

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) Pub Date : 2015-11-01 DOI: 10.1109/ISKE.2015.62

Mingtao Feng, Yaonan Wang, Chengzhong Wu

引用次数: 2

Fuzzy Image Segmentation Based on the Hierarchical Divide and Link Clustering Algorithm 基于层次分割和链接聚类算法的模糊图像分割

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) Pub Date : 2015-11-01 DOI: 10.1109/ISKE.2015.89

Carely Guada, D. Gómez, Juan Tinguaro Rodríguez, J. Yáñez, J. Montero

引用次数: 5

Non-clausal Multi-ary alpha-Ordered Linear Generalized Resolution Method for Lattice-Valued First-Order Logic 格值一阶逻辑的非子句多元序线性广义分解方法

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) Pub Date : 2015-11-01 DOI: 10.1109/ISKE.2015.84

Hairui Jia, Yi Liu, Yang Xu

引用次数: 0