Author: Lizhen Wang
Publisher: Springer Nature
ISBN: 981167566X
Category : Computers
Languages : en
Pages : 307
Book Description
The development of information technology has made it possible to collect large amounts of spatial data on a daily basis. It is of enormous significance when it comes to discovering implicit, non-trivial and potentially valuable information from this spatial data. Spatial co-location patterns reveal the distribution rules of spatial features, which can be valuable for application users. This book provides commercial software developers with proven and effective algorithms for detecting and filtering these implicit patterns, and includes easily implemented pseudocode for all the algorithms. Furthermore, it offers a basis for further research in this promising field. Preference-based co-location pattern mining refers to mining constrained or condensed co-location patterns instead of mining all prevalent co-location patterns. Based on the authors’ recent research, the book highlights techniques for solving a range of problems in this context, including maximal co-location pattern mining, closed co-location pattern mining, top-k co-location pattern mining, non-redundant co-location pattern mining, dominant co-location pattern mining, high utility co-location pattern mining, user-preferred co-location pattern mining, and similarity measures between spatial co-location patterns. Presenting a systematic, mathematical study of preference-based spatial co-location pattern mining, this book can be used both as a textbook for those new to the topic and as a reference resource for experienced professionals.
Preference-based Spatial Co-location Pattern Mining
Author: Lizhen Wang
Publisher: Springer Nature
ISBN: 981167566X
Category : Computers
Languages : en
Pages : 307
Book Description
The development of information technology has made it possible to collect large amounts of spatial data on a daily basis. It is of enormous significance when it comes to discovering implicit, non-trivial and potentially valuable information from this spatial data. Spatial co-location patterns reveal the distribution rules of spatial features, which can be valuable for application users. This book provides commercial software developers with proven and effective algorithms for detecting and filtering these implicit patterns, and includes easily implemented pseudocode for all the algorithms. Furthermore, it offers a basis for further research in this promising field. Preference-based co-location pattern mining refers to mining constrained or condensed co-location patterns instead of mining all prevalent co-location patterns. Based on the authors’ recent research, the book highlights techniques for solving a range of problems in this context, including maximal co-location pattern mining, closed co-location pattern mining, top-k co-location pattern mining, non-redundant co-location pattern mining, dominant co-location pattern mining, high utility co-location pattern mining, user-preferred co-location pattern mining, and similarity measures between spatial co-location patterns. Presenting a systematic, mathematical study of preference-based spatial co-location pattern mining, this book can be used both as a textbook for those new to the topic and as a reference resource for experienced professionals.
Publisher: Springer Nature
ISBN: 981167566X
Category : Computers
Languages : en
Pages : 307
Book Description
The development of information technology has made it possible to collect large amounts of spatial data on a daily basis. It is of enormous significance when it comes to discovering implicit, non-trivial and potentially valuable information from this spatial data. Spatial co-location patterns reveal the distribution rules of spatial features, which can be valuable for application users. This book provides commercial software developers with proven and effective algorithms for detecting and filtering these implicit patterns, and includes easily implemented pseudocode for all the algorithms. Furthermore, it offers a basis for further research in this promising field. Preference-based co-location pattern mining refers to mining constrained or condensed co-location patterns instead of mining all prevalent co-location patterns. Based on the authors’ recent research, the book highlights techniques for solving a range of problems in this context, including maximal co-location pattern mining, closed co-location pattern mining, top-k co-location pattern mining, non-redundant co-location pattern mining, dominant co-location pattern mining, high utility co-location pattern mining, user-preferred co-location pattern mining, and similarity measures between spatial co-location patterns. Presenting a systematic, mathematical study of preference-based spatial co-location pattern mining, this book can be used both as a textbook for those new to the topic and as a reference resource for experienced professionals.
Spatial Data and Intelligence
Author: Huayi Wu
Publisher: Springer Nature
ISBN: 3031245210
Category : Computers
Languages : en
Pages : 290
Book Description
This book constitutes the refereed proceedings of the Third International Conference, SpatialDI 2022, Wuhan, China, August 5–7, 2022, Revised Selected Papers. The 19 full papers and 1 short paper included in this book were carefully reviewed and selected from 77 submissions. They were organized in topical sections as follows: Traffic Management, Data science, City Analysis.
Publisher: Springer Nature
ISBN: 3031245210
Category : Computers
Languages : en
Pages : 290
Book Description
This book constitutes the refereed proceedings of the Third International Conference, SpatialDI 2022, Wuhan, China, August 5–7, 2022, Revised Selected Papers. The 19 full papers and 1 short paper included in this book were carefully reviewed and selected from 77 submissions. They were organized in topical sections as follows: Traffic Management, Data science, City Analysis.
Spatial and Temporal Databases
Author: Mario A. Nascimento
Publisher: Springer
ISBN: 3642402356
Category : Computers
Languages : en
Pages : 519
Book Description
This book constitutes the refereed proceedings of the 13th International Symposium on Spatial and Temporal Databases, SSTD 2013, held in Munich, Germany, in August 2013. The 24 revised full papers presented were carefully reviewed and selected from 58 submissions. The papers are organized in topical sections on joins and algorithms; mining and discovery; indexing; trajectories and road network data; nearest neighbours queries; uncertainty; and demonstrations.
Publisher: Springer
ISBN: 3642402356
Category : Computers
Languages : en
Pages : 519
Book Description
This book constitutes the refereed proceedings of the 13th International Symposium on Spatial and Temporal Databases, SSTD 2013, held in Munich, Germany, in August 2013. The 24 revised full papers presented were carefully reviewed and selected from 58 submissions. The papers are organized in topical sections on joins and algorithms; mining and discovery; indexing; trajectories and road network data; nearest neighbours queries; uncertainty; and demonstrations.
Big Data and Social Computing
Author: Xiaofeng Meng
Publisher: Springer Nature
ISBN: 9819939259
Category : Computers
Languages : en
Pages : 412
Book Description
This book constitutes refereed proceedings of the 8th China National Conference on Big Data and Social Computing, BDSC 2023, held in Urumqi, China, from July 15–17, 2023. The 23 full papers and 3 short papers presented in this volume were carefully reviewed and selected from a total of 141 submissions. The papers in the volume are organized according to the following topical headings: Digital Technology and Sustainable Development; Social Network and Group Behavior; Digital infrastructure and the Intelligent Society; Digital Society and Public Security; Artificial Intelligence and Cognitive Science; and Internet Intelligent Algorithm Governance.
Publisher: Springer Nature
ISBN: 9819939259
Category : Computers
Languages : en
Pages : 412
Book Description
This book constitutes refereed proceedings of the 8th China National Conference on Big Data and Social Computing, BDSC 2023, held in Urumqi, China, from July 15–17, 2023. The 23 full papers and 3 short papers presented in this volume were carefully reviewed and selected from a total of 141 submissions. The papers in the volume are organized according to the following topical headings: Digital Technology and Sustainable Development; Social Network and Group Behavior; Digital infrastructure and the Intelligent Society; Digital Society and Public Security; Artificial Intelligence and Cognitive Science; and Internet Intelligent Algorithm Governance.
Intelligent Information Processing XI
Author: Zhongzhi Shi
Publisher: Springer Nature
ISBN: 3031039483
Category : Computers
Languages : en
Pages : 560
Book Description
This book constitutes the refereed proceedings of the 12th IFIP TC 12 International Conference on Intelligent Information Processing, IIP 2022, held in Qingdao, China, in July 2022. The 37 full papers and 6 short papers presented were carefully reviewed and selected from 57 submissions. They are organized in topical sections on Machine Learning, Data Mining, Multiagent Systems, Social Computing, Blockchain Technology, Game Theory and Emotion, Pattern Recognition, Image Processing and Applications.
Publisher: Springer Nature
ISBN: 3031039483
Category : Computers
Languages : en
Pages : 560
Book Description
This book constitutes the refereed proceedings of the 12th IFIP TC 12 International Conference on Intelligent Information Processing, IIP 2022, held in Qingdao, China, in July 2022. The 37 full papers and 6 short papers presented were carefully reviewed and selected from 57 submissions. They are organized in topical sections on Machine Learning, Data Mining, Multiagent Systems, Social Computing, Blockchain Technology, Game Theory and Emotion, Pattern Recognition, Image Processing and Applications.
Advanced Data Mining and Applications
Author: Ronghuai Huang
Publisher: Springer
ISBN: 3642033482
Category : Computers
Languages : en
Pages : 826
Book Description
This volume contains the proceedings of the International Conference on Advanced Data Mining and Applications (ADMA 2009), held in Beijing, China, during August 17–19, 2009. We are pleased to have a very strong program. Acceptance into the conference proceedings was extremely competitive. From the 322 submissions from 27 countries and regions, the Program Committee selected 34 full papers and 47 short papers for presentation at the conference and inclusion in the proceedings. The c- tributed papers cover a wide range of data mining topics and a diverse spectrum of interesting applications. The Program Committee worked very hard to select these papers through a rigorous review process and extensive discussion, and finally c- posed a diverse and exciting program for ADMA 2009. An important feature of the main program was the truly outstanding keynote spe- ers program. Edward Y. Chang, Director of Research, Google China, gave a talk titled "Confucius and 'Its' Intelligent Disciples". Being right in the forefront of data mining applications to the world's largest knowledge and data base, the Web, Dr. Chang - scribed how Google's Knowledge Search product help to improve the scalability of machine learning for Web-scale applications. Charles X. Ling, a seasoned researcher in data mining from the University of Western Ontario, Canada, talked about his in- vative applications of data mining and artificial intelligence to gifted child education.
Publisher: Springer
ISBN: 3642033482
Category : Computers
Languages : en
Pages : 826
Book Description
This volume contains the proceedings of the International Conference on Advanced Data Mining and Applications (ADMA 2009), held in Beijing, China, during August 17–19, 2009. We are pleased to have a very strong program. Acceptance into the conference proceedings was extremely competitive. From the 322 submissions from 27 countries and regions, the Program Committee selected 34 full papers and 47 short papers for presentation at the conference and inclusion in the proceedings. The c- tributed papers cover a wide range of data mining topics and a diverse spectrum of interesting applications. The Program Committee worked very hard to select these papers through a rigorous review process and extensive discussion, and finally c- posed a diverse and exciting program for ADMA 2009. An important feature of the main program was the truly outstanding keynote spe- ers program. Edward Y. Chang, Director of Research, Google China, gave a talk titled "Confucius and 'Its' Intelligent Disciples". Being right in the forefront of data mining applications to the world's largest knowledge and data base, the Web, Dr. Chang - scribed how Google's Knowledge Search product help to improve the scalability of machine learning for Web-scale applications. Charles X. Ling, a seasoned researcher in data mining from the University of Western Ontario, Canada, talked about his in- vative applications of data mining and artificial intelligence to gifted child education.
Spatial Data and Intelligence
Author: Xiaofeng Meng
Publisher: Springer Nature
ISBN: 3031329104
Category : Computers
Languages : en
Pages : 274
Book Description
This book constitutes the refereed proceedings of the 4th International Conference on Spatial Data and Intelligence, SpatialDI 2023, held in Nanchang, China, in April 13–15, 2023. The 18 full papers included in this book were carefully reviewed and selected from 68 submissions. They were organized in topical sections as follows: traffic management; visualization analysis; spatial big data analysis; spatiotemporal data mining; spatiotemporal data storage; and metaverse.
Publisher: Springer Nature
ISBN: 3031329104
Category : Computers
Languages : en
Pages : 274
Book Description
This book constitutes the refereed proceedings of the 4th International Conference on Spatial Data and Intelligence, SpatialDI 2023, held in Nanchang, China, in April 13–15, 2023. The 18 full papers included in this book were carefully reviewed and selected from 68 submissions. They were organized in topical sections as follows: traffic management; visualization analysis; spatial big data analysis; spatiotemporal data mining; spatiotemporal data storage; and metaverse.
Machine Learning and Knowledge Discovery in Databases
Author: Wray Buntine
Publisher: Springer Science & Business Media
ISBN: 3642041736
Category : Computers
Languages : en
Pages : 787
Book Description
This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2009, held in Bled, Slovenia, in September 2009. The 106 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 422 paper submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.
Publisher: Springer Science & Business Media
ISBN: 3642041736
Category : Computers
Languages : en
Pages : 787
Book Description
This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2009, held in Bled, Slovenia, in September 2009. The 106 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 422 paper submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.
Innovative Computing and Communications
Author: Aboul Ella Hassanien
Publisher: Springer Nature
ISBN: 9819738172
Category :
Languages : en
Pages : 694
Book Description
Publisher: Springer Nature
ISBN: 9819738172
Category :
Languages : en
Pages : 694
Book Description
Advances in Knowledge Discovery and Data Mining
Author: Jinho Kim
Publisher: Springer
ISBN: 3319575295
Category : Computers
Languages : en
Pages : 876
Book Description
This two-volume set, LNAI 10234 and 10235, constitutes the thoroughly refereed proceedings of the 21st Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2017, held in Jeju, South Korea, in May 2017. The 129 full papers were carefully reviewed and selected from 458 submissions. They are organized in topical sections named: classification and deep learning; social network and graph mining; privacy-preserving mining and security/risk applications; spatio-temporal and sequential data mining; clustering and anomaly detection; recommender system; feature selection; text and opinion mining; clustering and matrix factorization; dynamic, stream data mining; novel models and algorithms; behavioral data mining; graph clustering and community detection; dimensionality reduction.
Publisher: Springer
ISBN: 3319575295
Category : Computers
Languages : en
Pages : 876
Book Description
This two-volume set, LNAI 10234 and 10235, constitutes the thoroughly refereed proceedings of the 21st Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2017, held in Jeju, South Korea, in May 2017. The 129 full papers were carefully reviewed and selected from 458 submissions. They are organized in topical sections named: classification and deep learning; social network and graph mining; privacy-preserving mining and security/risk applications; spatio-temporal and sequential data mining; clustering and anomaly detection; recommender system; feature selection; text and opinion mining; clustering and matrix factorization; dynamic, stream data mining; novel models and algorithms; behavioral data mining; graph clustering and community detection; dimensionality reduction.