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Data mining for customer service support

S.C. Hui, G. Jha
2000 Information & Management  
In addition, a data mining technique that integrates neural network, case-based reasoning, and rule-based reasoning is proposed; it would search the unstructured customer service records for machine fault  ...  This paper investigates how to apply data mining techniques to extract knowledge from the database to support two kinds of customer service activities: decision support and machine fault diagnosis.  ...  The neural network model generation phase extracts the knowledge from the fault-conditions to train the neural network to build neural network models for classi®cation and clustering.  ... 
doi:10.1016/s0378-7206(00)00051-3 fatcat:gxpit6fyy5bwhlqyk4qo2j3neu

A Research of Cement Energy-Saving KM System Based on CBR and BP Neural Network

An Ji-Yu, Zhu Xiao-Hui, Ma Yong-Qiang
2013 Sensors & Transducers  
The model joins BP neural network technology to the case organization index and retrieval stage of case-based reasoning, which makes up for the defect of traditional case-based reasoning.  ...  This paper analyzes the advantages of case-based reasoning and BP neural network in case retrieval, and combines the features respectively to design the BP-CBR case retrieval model.  ...  BP neural network structure. Fig. 3 . 3 The KF network of energy-saving reconstruction case. Fig. 4 . 4 BP-CBR case retrieval model.  ... 
doaj:3b847f3c193e4debba570fb17623c00c fatcat:mq2xpo2y4jbpfli5ivrc2pvy5y

DISA: A Scientific Writing Advisor with Deep Information Structure Analysis

Hen-Hsen Huang, Hsin-Hsi Chen
2017 Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence  
This paper demonstrates DISA, a higher-level writing assistant system, which analyzes the information structure of abstracts, and retrieves the knowledge according to the research goals from the related  ...  By incorporating the latest neural-network technologies including linguistically-informed neural-network and autoencoder, we construct an intelligent system which extends the scope of computer-aided writing  ...  We thank the Writing Center at National Tsing Hua University for providing us the NTHU Academic Writing Database.  ... 
doi:10.24963/ijcai.2017/773 dblp:conf/ijcai/HuangC17 fatcat:xmnwe3xwjbcqloos3efqugfi2m

Deep Learning for Information Retrieval

Hang Li, Zhengdong Lu
2016 Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval - SIGIR '16  
In the first part, we introduce the fundamental techniques of deep learning for natural language processing and information retrieval, such as word embedding, recurrent neural networks, and convolutional  ...  neural networks.  ...  a deep neural network to automatically conduct question answering from the database or knowledge base.  ... 
doi:10.1145/2911451.2914800 dblp:conf/sigir/LiL16 fatcat:fosiii4wt5fv5lyv52ntc3afna

Natural Language QA Approaches using Reasoning with External Knowledge [article]

Chitta Baral, Pratyay Banerjee, Kuntal Kumar Pal, Arindam Mitra
2020 arXiv   pre-print
Question answering (QA) in natural language (NL) has been an important aspect of AI from its early days. Winograd's "councilmen" example in his 1972 paper and McCarthy's Mr.  ...  external knowledge plays an important role.  ...  This is the challenge for knowledge retrieval from structured knowledge bases.  ... 
arXiv:2003.03446v1 fatcat:5ssmvcdzajc5flasg3s5hsfxsu

A SURVEY ON WEB MINING TECHNIQUES

K. Velkumar, Dr. P. Thendral
2020 International Journal of Recent Trends in Engineering and Research  
Web Content mining retrieve knowledge from the content of web documents. Web structure mining is retrieve the structure information from the web.  ...  So, it becomes a challenging task to retrieve useful and novel information and knowledge from this huge, dynamic structurally complex and ever-growing World Wide Web.  ...  Intelligent search engine, information filtering and personalized web agents. b) Web structure mining The web structure mining is retrieve the structural information from the world wide web.  ... 
doi:10.23883/ijrter.conf.20200315.027.x6bxa fatcat:c5ptduil2bgjfjrtli5crqpu2i

Intelligent approaches to performance support

Philip Barker, Stephen Richards, Ashok Banerji
2011 Research in Learning Technology  
This paper discusses the design of a distributed electronic performance support system and the ways in which 'intelligent agents' based on expert systems and neural networks can be used to locate and share  ...  They also provide efficient and effective ways of enabling the knowledge and expertise within an organization to be shared.  ...  This query is passed, along with the appropriate neural-net information from the database, to the neural network engine.  ... 
doi:10.3402/rlt.v2i1.9575 fatcat:6fmiy4o7j5emfb6d5isgyqusoy

Intelligent approaches to performance support

Philip Barker, Stephen Richards, Ashok Banerji
1994 Research in Learning Technology  
This paper discusses the design of a distributed electronic performance support system and the ways in which 'intelligent agents' based on expert systems and neural networks can be used to locate and share  ...  They also provide efficient and effective ways of enabling the knowledge and expertise within an organization to be shared.  ...  This query is passed, along with the appropriate neural-net information from the database, to the neural network engine.  ... 
doi:10.1080/0968776940020109 fatcat:w2thes3qnnhizloyh5b4hhxxy4

A Deep Look into Neural Ranking Models for Information Retrieval [article]

Jiafeng Guo, Yixing Fan, Liang Pang, Liu Yang, Qingyao Ai, Hamed Zamani, Chen Wu, W. Bruce Croft, Xueqi Cheng
2019 arXiv   pre-print
Ranking models lie at the heart of research on information retrieval (IR).  ...  The power of neural ranking models lies in the ability to learn from the raw text inputs for the ranking problem to avoid many limitations of hand-crafted features.  ...  within conversations.Beyond structured knowledge in knowledge bases, other research has explored how to integrate external knowledge from unstructured texts, which are more common for information on the  ... 
arXiv:1903.06902v3 fatcat:j22ic7foibcurp45b4amdiwfhu

Page 16 of The Information Management Journal Vol. 29, Issue 4 [page]

1995 The Information Management Journal  
Another neural network system, called AIR (Adaptive Information Retrieval),9! was developed using a similar approach and with the same goal of information retrieval.  ...  Records management, library and information work are very suitable fields for the application of neural networks.  ... 

Intelligent Search for Distributed Information Sources Using Heterogeneous Neural Networks [chapter]

Hui Yang, Minjie Zhang
2003 Lecture Notes in Computer Science  
This preliminary investigation suggests that Neural Networks are useful tools for intelligent search for distributed information sources.  ...  This paper shows how heterogeneous neural networks can be used in the design of an intelligent distributed information retrieval (DIR) system.  ...  In Section 2, we first present an overview of neural network techniques for information retrieval.  ... 
doi:10.1007/3-540-36901-5_52 fatcat:7tohw7l6rnfzzg62dzgxbzo3tu

Neural Ranking Models for Document Retrieval [article]

Mohamed Trabelsi, Zhiyu Chen, Brian D. Davison, Jeff Heflin
2021 arXiv   pre-print
A variety of deep learning models have been proposed, and each model presents a set of neural network components to extract features that are used for ranking.  ...  Recently, researchers have leveraged deep learning models in information retrieval.  ...  Human activity recognition using recurrent neural networks. In Machine Learning and Knowledge Liu, W., Jia, Y., Sermanet, P., Reed, S.  ... 
arXiv:2102.11903v1 fatcat:zc2otf456rc2hj6b6wpcaaslsa

Task-Oriented Conversation Generation Using Heterogeneous Memory Networks [article]

Zehao Lin, Xinjing Huang, Feng Ji, Haiqing Chen, Ying Zhang
2019 arXiv   pre-print
How to incorporate external knowledge into a neural dialogue model is critically important for dialogue systems to behave like real humans.  ...  However, existing memory networks do not perform well when leveraging heterogeneous information from different sources.  ...  This work was supported by the NSFC (No.61402403), DAMO Academy (Alibaba Group), Alibaba-Zhejiang University Joint Institute of Frontier Technologies, Chinese Knowledge Center for Engineering Sciences  ... 
arXiv:1909.11287v1 fatcat:lilx5hyyljej7janwebybltzau

Task-Oriented Conversation Generation Using Heterogeneous Memory Networks

Zehao Lin, Xinjing Huang, Feng Ji, Haiqing Chen, Yin Zhang
2019 Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)  
How to incorporate external knowledge into a neural dialogue model is critically important for dialogue systems to behave like real humans.  ...  However, existing memory networks do not perform well when leveraging heterogeneous information from different sources.  ...  This work was supported by the NSFC (No.61402403), DAMO Academy (Alibaba Group), Alibaba-Zhejiang University Joint Institute of Frontier Technologies, Chinese Knowledge Center for Engineering Sciences  ... 
doi:10.18653/v1/d19-1463 dblp:conf/emnlp/LinHJCZ19 fatcat:djelamkro5cpvi3qo5zpuftfne

Integrating Symbol-Oriented and Sub-Symbolic Reasoning Methods into Hybrid Systems [chapter]

Franz J. Kurfess
2002 From Synapses to Rules  
Many of these methods are based on neural network techniques, which typically represent and process knowledge at a level below symbols; this is often referred to as sub-symbolic representation.  ...  This works reasonably well in situations where knowledge is available in explicit form, typically through experts or written documents.  ...  Neural networks can be helpful with knowledge acquisition due to their capability to learn from examples.  ... 
doi:10.1007/978-1-4615-0705-5_14 fatcat:yivvfaup5zbdpcrau5uxenfoo4
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