Data science is not only about numbers and how to crunch them; it is also about how to communicate project results with the various audience. Scientific journals and conferences are an excellent venue for getting a wider audience reach and gathering valuable comments. The talk will answer the questions: How to structure a scientific paper in data science? What are relevant venues for showcasing your work to gain the most relevant reach? To demystify the process of scientific writing, the case study will be presented: Messy process: Story of the birth of one data science paper.
The document discusses databases research and provides information about important organizations in the field like ACM and IEEE. It outlines topics covered at database conferences and gives tips for finding relevant information sources like journal papers, conference papers, textbooks, company websites, and academic search engines and databases. Good sources are identified as including ArXiv, DBLP, and digital libraries. Research papers are described as typically containing sections for the title, abstract, introduction, methodology, results, and bibliography.
Data Science and AI in Biomedicine: The World has ChangedPhilip Bourne
This document discusses the changing landscape of data science and AI in biomedicine. Some key points:
- We are at a tipping point where data science is becoming a driver of biomedical research rather than just a tool. Biomedical researchers need to become data scientists.
- Data science is interdisciplinary and touches every field due to the rise of digital data. It requires openness, translation of findings, and consideration of responsibilities like algorithmic bias.
- Advances like AlphaFold2 show the power of large collaborative efforts combining data, computing resources, engineering, and domain expertise. This points to the need for public-private partnerships and new models of open data sharing.
- The definition of
In the last decade, several Scientific Knowledge Graphs (SKG) were released, representing scientific knowledge in a structured, interlinked, and semantically rich manner. But, what kind of information they describe? How they have been built? What can we do with them? In this lecture, I will first provide an overview of well-known SKGs, like Microsoft Academic Graph, Dimensions, and others. Then, I will present the Academia/Industry DynAmics (AIDA) Knowledge Graph, which describes 21M publications and 8M patents according to i) the research topics drawn from the Computer Science Ontology, ii) the type of the author's affiliations (e.g, academia, industry), and iii) 66 industrial sectors (e.g., automotive, financial, energy, electronics) from the Industrial Sectors Ontology (INDUSO). Finally, I will showcase a number of tools and approaches using such SKGs, supporting researchers, companies, and policymakers in making sense of research dynamics.
Data Science - An emerging Stream of Science with its Spreading Reach & ImpactDr. Sunil Kr. Pandey
This is my presentation on the Topic "Data Science - An emerging Stream of Science with its Spreading Reach & Impact". I have compiled and collected different statistics and data from different sources. This may be useful for students and those who might be interested in this field of Study.
The document discusses the evolution of e-Research, from early forms like supercomputing and grid computing to current approaches like big data. It argues that e-Research will become so integrated into normal research practices that it will effectively disappear as a separate field. The document also provides examples of how computational approaches are transforming different domains like the sciences, social sciences, humanities, and arts. It analyzes the digitization of cultural artifacts and large-scale text analysis as novel advances enabled by e-Research.
The 15th International Conference on Knowledge, Information and Creativity Support System (KICSS2020) will be held online on November 25-26, 2020 and hosted by D-Agree. The conference aims to facilitate technology and knowledge exchange between international researchers in fields related to knowledge science, information systems, creativity support systems, and complex systems modeling. It will cover a broad range of topics related to knowledge engineering, information technology, creativity support systems, and complex systems modeling.
Data Mining Xuequn Shang NorthWestern Polytechnical Universitybutest
This document provides information about a data mining course, including the course schedule, evaluation criteria, and topics to be covered. The course will take place on Tuesday and Friday evenings from 7-9pm, and will be taught by Xuequn Shang. Topics include association analysis, sequential pattern mining, classification, clustering, and data preprocessing. Students will be evaluated based on assignments, class participation, a project, and a final exam.
Building the FAIR Research Commons: A Data Driven Society of ScientistsCarole Goble
Science is knowledge work. The scientific method and scholarly communication are about facilitating “knowledge turns” – that is, the turning of observation and hypothesis through experimentation, comparison, and analysis into new, pooled knowledge. Turns depend on the FAIR flow and availability of data, methods for automated processing, reproducible results and on a society of scientists coordinating and collaborating. We need to build a new form of Research Commons and I will present my steps towards this.
Presented at Symposium: The Future of a Data-Driven Society, Maastricht University, 25 Jan 2018 that accompanied the 42nd Dies Natalis where I was awarded an honorary doctorate
Personal video:
https://www.youtube.com/watch?v=k5WN6KDDatU&index=4&list=PLzi-FBaZlOOagma5dCW7WSA5lv22tmNMD
Video of the symposium:
https://www.youtube.com/watch?v=JN9eMMtCHf8&t=19s&index=6&list=PLzi-FBaZlOOagma5dCW7WSA5lv22tmNMD
The document discusses databases research and provides information about important organizations in the field like ACM and IEEE. It outlines topics covered at database conferences and gives tips for finding relevant information sources like journal papers, conference papers, textbooks, company websites, and academic search engines and databases. Good sources are identified as including ArXiv, DBLP, and digital libraries. Research papers are described as typically containing sections for the title, abstract, introduction, methodology, results, and bibliography.
Data Science and AI in Biomedicine: The World has ChangedPhilip Bourne
This document discusses the changing landscape of data science and AI in biomedicine. Some key points:
- We are at a tipping point where data science is becoming a driver of biomedical research rather than just a tool. Biomedical researchers need to become data scientists.
- Data science is interdisciplinary and touches every field due to the rise of digital data. It requires openness, translation of findings, and consideration of responsibilities like algorithmic bias.
- Advances like AlphaFold2 show the power of large collaborative efforts combining data, computing resources, engineering, and domain expertise. This points to the need for public-private partnerships and new models of open data sharing.
- The definition of
In the last decade, several Scientific Knowledge Graphs (SKG) were released, representing scientific knowledge in a structured, interlinked, and semantically rich manner. But, what kind of information they describe? How they have been built? What can we do with them? In this lecture, I will first provide an overview of well-known SKGs, like Microsoft Academic Graph, Dimensions, and others. Then, I will present the Academia/Industry DynAmics (AIDA) Knowledge Graph, which describes 21M publications and 8M patents according to i) the research topics drawn from the Computer Science Ontology, ii) the type of the author's affiliations (e.g, academia, industry), and iii) 66 industrial sectors (e.g., automotive, financial, energy, electronics) from the Industrial Sectors Ontology (INDUSO). Finally, I will showcase a number of tools and approaches using such SKGs, supporting researchers, companies, and policymakers in making sense of research dynamics.
Data Science - An emerging Stream of Science with its Spreading Reach & ImpactDr. Sunil Kr. Pandey
This is my presentation on the Topic "Data Science - An emerging Stream of Science with its Spreading Reach & Impact". I have compiled and collected different statistics and data from different sources. This may be useful for students and those who might be interested in this field of Study.
The document discusses the evolution of e-Research, from early forms like supercomputing and grid computing to current approaches like big data. It argues that e-Research will become so integrated into normal research practices that it will effectively disappear as a separate field. The document also provides examples of how computational approaches are transforming different domains like the sciences, social sciences, humanities, and arts. It analyzes the digitization of cultural artifacts and large-scale text analysis as novel advances enabled by e-Research.
The 15th International Conference on Knowledge, Information and Creativity Support System (KICSS2020) will be held online on November 25-26, 2020 and hosted by D-Agree. The conference aims to facilitate technology and knowledge exchange between international researchers in fields related to knowledge science, information systems, creativity support systems, and complex systems modeling. It will cover a broad range of topics related to knowledge engineering, information technology, creativity support systems, and complex systems modeling.
Data Mining Xuequn Shang NorthWestern Polytechnical Universitybutest
This document provides information about a data mining course, including the course schedule, evaluation criteria, and topics to be covered. The course will take place on Tuesday and Friday evenings from 7-9pm, and will be taught by Xuequn Shang. Topics include association analysis, sequential pattern mining, classification, clustering, and data preprocessing. Students will be evaluated based on assignments, class participation, a project, and a final exam.
Building the FAIR Research Commons: A Data Driven Society of ScientistsCarole Goble
Science is knowledge work. The scientific method and scholarly communication are about facilitating “knowledge turns” – that is, the turning of observation and hypothesis through experimentation, comparison, and analysis into new, pooled knowledge. Turns depend on the FAIR flow and availability of data, methods for automated processing, reproducible results and on a society of scientists coordinating and collaborating. We need to build a new form of Research Commons and I will present my steps towards this.
Presented at Symposium: The Future of a Data-Driven Society, Maastricht University, 25 Jan 2018 that accompanied the 42nd Dies Natalis where I was awarded an honorary doctorate
Personal video:
https://www.youtube.com/watch?v=k5WN6KDDatU&index=4&list=PLzi-FBaZlOOagma5dCW7WSA5lv22tmNMD
Video of the symposium:
https://www.youtube.com/watch?v=JN9eMMtCHf8&t=19s&index=6&list=PLzi-FBaZlOOagma5dCW7WSA5lv22tmNMD
Data Science Meets Biomedicine, Does Anything ChangePhilip Bourne
Data science is driving major changes in biomedical research by enabling new types of integrative, multi-scale analyses. However, biomedical research may no longer lead data science due to a lack of comprehensive data infrastructure and cultural barriers. Responsible data science that balances openness, ethics, and benefiting patients could help establish biomedicine's continued leadership role. Major challenges include limited resources, attracting diverse talent, and prioritizing strategic initiatives over conforming to traditional models of research.
Acting as Advocate? Seven steps for libraries in the data decadeLizLyon
UKOLN advocates that libraries take seven steps to support data management and open science in the data decade:
1) Provide briefings on cloud data services in partnership with IT services.
2) Build usable data management tools in partnership with researchers.
3) Develop data sustainability strategies and articulate the costs and benefits.
4) Publish case studies on open science to show benefits of universal data sharing.
5) Present at university ethics committees to highlight open data issues.
6) Raise awareness of citizen science opportunities and guidelines for good practice.
7) Promote data citation and attribution to embed in publication practice.
4 th International Conference on Data Science and Machine Learning (DSML 2023)gerogepatton
4
th International Conference on Data Science and Machine Learning (DSML 2023) will
act as a major forum for the presentation of innovative ideas, approaches, developments, and
research projects in the areas of Data Science and Machine Learning. It will also serve to
facilitate the exchange of information between researchers and industry professionals to
discuss the latest issues and advancement in the area of Data Science and Machine Learning.
Authors are solicited to contribute to the Conference by submitting articles that illustrate
research results, projects, surveying works and industrial experiences that describe significant
advances in the Computer Networks & Communications.
OSFair2017 training | Explore, model, analyze and visualize systematic resear...Open Science Fair
1. Text mining and topic modeling of large volumes of scholarly literature can provide insights into research trends, collaboration patterns, and emerging topics.
2. A probabilistic multi-view topic model analyzes text alongside structured metadata to discover topics across full text articles and related entities.
3. Visualization of topic modeling results shows how topics change over time, identifies trending and declining areas of research, and reveals relationships between authors, topics, and other metadata.
OII Summer Doctoral Programme 2010: Global brain by Meyer & SchroederEric Meyer
The document discusses how technology is driving research to become more collaborative globally through distributed and networked tools. It examines several case studies where technologies enabled large-scale collaborative research projects that addressed questions too big for individual labs. These include distributed computing for particle physics, genomic studies, and proteomics. Challenges discussed include interoperability, data sharing policies, and sustaining momentum in infrastructure.
9th International Conference on Data Mining and Database Management Systems (...civejjour
#PhD #education #research #publication #Education#international #everyone
#Data Mining #Data mining Applications #Data Mining Algorithms #XML and Databases #Information Systems #Digital Libraries #Process Modelling #Database Management Systems
==============================
CALL FOR ARTICLES-CURRENT ISSUE...!
9th International Conference on Data Mining and Database Management Systems (DMDBS 2023)
December 16 ~ 17, 2023, Dubai, UAE
https://csea2023.org/dmdbs/index
Paper Submission
Authors are invited to submit papers through the conference Submission System by July 30, 2023.
Submission Deadline: July 30, 2023
Contact Us ;dmdbs@csea2023.org or dmdbsconf@yahoo.com
Submission URL :https://csea2023.org/submission/index.php
The document discusses future developments in cognitive-based knowledge acquisition systems using big data. It covers preparing students and the cognitive landscape for big data analytics through tools like concept maps and visualization. It also addresses challenges like determining where information comes from, whether humans or computers can best identify patterns in data, and whether autonomous systems will eventually replace human decision making.
4th International Conference on Data Science and Machine Learning (DSML 2023) gerogepatton
4th International Conference on Data Science and Machine Learning (DSML 2023) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Data Science and Machine Learning. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Data Science and Machine Learning.
Authors are solicited to contribute to the Conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the Computer Networks & Communications.
Una breve introduzione alla data science e al machine learning con un'enfasi sugli scenari applicativi, da quelli tradizionali a quelli più innovativi. La overview copre la definizione di base di data science, una overview del machine learning e esempi su scenari tradizionali, Recommender systems e Social Network Analysis, IoT e Deep Learning
Applying machine learning techniques to big data in the scholarly domainAngelo Salatino
Slides of the Lecture at the 5th International School on Applied Probability Theory,Communications Technologies & Data Science (APTCT-2020)
12 Nov 2020
This document discusses managing research data for open science based on the UK experience. It outlines key aspects of open science such as making research more open, global, collaborative and closer to society. The document discusses mandates for open research data from funding bodies in the UK and EU, including stipulations in Horizon 2020 and requirements from EPSRC. It defines what constitutes research data and examines challenges around research data management, including technology issues, people issues, policy issues and resources. The importance of data skills training for researchers and data professionals is also covered.
Submit Your Research Papers - International Conference on AI, Data Mining and...ijistjournal
International Conference on AI, Data Mining and Data Science (AIDD 2023) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence, Data mining, and Data Science. The Conference looks for significant contributions to all major fields of the AI, Data mining, and Data Science in theoretical and practical aspects.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:
Presentación Ciro Cattuto, ISI Foundation en VI Summit País Digital 2018PAÍS DIGITAL
Exposición “ Data Science for private and public good” de Ciro Cattuto, Scientific Director, ISI Foundation, en el marco del VI Summit País Digital 2018, realizado el 4 y 5 de septiembre en Santiago, Chile.
Linked Open Data about Springer Nature conferences. The story so farAliaksandr Birukou
Despite many efforts for making data about scholarly publications available on the Web of Data, lots of information about academic conferences is still contained in (at best) free-text format. When available in a structured format, these data would provide an essential input for the decisions researchers, libraries, publishers, funding and evaluation bodies take every day.
This talk will describe the project about having such data available as Linked Open Data (LOD) at lod.springer.com for around 10,000 computer science conferences. In addition, we will have a closer look at the lessons learnt from launching this portal and cover other Linked Data projects in Springer Nature. Finally, a novel semi-automated approach for classifying conference proceedings in Springer Nature will also be presented.
Submit Your Research Articles - International Conference on AI, Data Mining a...IJNSA Journal
International Conference on AI, Data Mining and Data Science (AIDD 2023) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence, Data mining, and Data Science. The Conference looks for significant contributions to all major fields of the AI, Data mining, and Data Science in theoretical and practical aspects.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:
Call for Research Articles - International Conference on AI, Data Mining and ...ijistjournal
International Conference on AI, Data Mining and Data Science (AIDD 2023) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence, Data mining, and Data Science. The Conference looks for significant contributions to all major fields of the AI, Data mining, and Data Science in theoretical and practical aspects.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:
Data Science is an interdisciplinary approach that combines computational science, statistics, and domain knowledge to extract meaningful insights from large and complex data. It aims to address challenges posed by the data revolution characterized by big data from diverse sources. There is no single agreed upon definition, but most definitions emphasize applying techniques from computer science, statistics, and the relevant domain area to discover patterns, make predictions, and support decision making from data. Key aspects include developing appropriate methodologies for knowledge discovery, forecasting and decisions using large and diverse data from sources like surveys, social media, sensors and more. The integration of domain knowledge representation with computational and statistical tools is seen as an important novelty that can enhance data analysis and interpretation.
A Comparative Study of Various Data Mining Techniques: Statistics, Decision T...Editor IJCATR
In this paper we focus on some techniques for solving data mining tasks such as: Statistics, Decision Trees and Neural
Networks. The new approach has succeed in defining some new criteria for the evaluation process, and it has obtained valuable results
based on what the technique is, the environment of using each techniques, the advantages and disadvantages of each technique, the
consequences of choosing any of these techniques to extract hidden predictive information from large databases, and the methods of
implementation of each technique. Finally, the paper has presented some valuable recommendations in this field.
The document provides an introduction to the concept of data mining. It discusses the evolution of data analysis techniques from empirical to computational to data-driven approaches. Data mining is presented as a natural evolution to analyze massive data sets and discover useful patterns. Key aspects of data mining covered include its functionality, types of data and knowledge that can be mined, major issues, and its relationship to other fields such as machine learning, statistics, and databases.
Data Science Meets Biomedicine, Does Anything ChangePhilip Bourne
Data science is driving major changes in biomedical research by enabling new types of integrative, multi-scale analyses. However, biomedical research may no longer lead data science due to a lack of comprehensive data infrastructure and cultural barriers. Responsible data science that balances openness, ethics, and benefiting patients could help establish biomedicine's continued leadership role. Major challenges include limited resources, attracting diverse talent, and prioritizing strategic initiatives over conforming to traditional models of research.
Acting as Advocate? Seven steps for libraries in the data decadeLizLyon
UKOLN advocates that libraries take seven steps to support data management and open science in the data decade:
1) Provide briefings on cloud data services in partnership with IT services.
2) Build usable data management tools in partnership with researchers.
3) Develop data sustainability strategies and articulate the costs and benefits.
4) Publish case studies on open science to show benefits of universal data sharing.
5) Present at university ethics committees to highlight open data issues.
6) Raise awareness of citizen science opportunities and guidelines for good practice.
7) Promote data citation and attribution to embed in publication practice.
4 th International Conference on Data Science and Machine Learning (DSML 2023)gerogepatton
4
th International Conference on Data Science and Machine Learning (DSML 2023) will
act as a major forum for the presentation of innovative ideas, approaches, developments, and
research projects in the areas of Data Science and Machine Learning. It will also serve to
facilitate the exchange of information between researchers and industry professionals to
discuss the latest issues and advancement in the area of Data Science and Machine Learning.
Authors are solicited to contribute to the Conference by submitting articles that illustrate
research results, projects, surveying works and industrial experiences that describe significant
advances in the Computer Networks & Communications.
OSFair2017 training | Explore, model, analyze and visualize systematic resear...Open Science Fair
1. Text mining and topic modeling of large volumes of scholarly literature can provide insights into research trends, collaboration patterns, and emerging topics.
2. A probabilistic multi-view topic model analyzes text alongside structured metadata to discover topics across full text articles and related entities.
3. Visualization of topic modeling results shows how topics change over time, identifies trending and declining areas of research, and reveals relationships between authors, topics, and other metadata.
OII Summer Doctoral Programme 2010: Global brain by Meyer & SchroederEric Meyer
The document discusses how technology is driving research to become more collaborative globally through distributed and networked tools. It examines several case studies where technologies enabled large-scale collaborative research projects that addressed questions too big for individual labs. These include distributed computing for particle physics, genomic studies, and proteomics. Challenges discussed include interoperability, data sharing policies, and sustaining momentum in infrastructure.
9th International Conference on Data Mining and Database Management Systems (...civejjour
#PhD #education #research #publication #Education#international #everyone
#Data Mining #Data mining Applications #Data Mining Algorithms #XML and Databases #Information Systems #Digital Libraries #Process Modelling #Database Management Systems
==============================
CALL FOR ARTICLES-CURRENT ISSUE...!
9th International Conference on Data Mining and Database Management Systems (DMDBS 2023)
December 16 ~ 17, 2023, Dubai, UAE
https://csea2023.org/dmdbs/index
Paper Submission
Authors are invited to submit papers through the conference Submission System by July 30, 2023.
Submission Deadline: July 30, 2023
Contact Us ;dmdbs@csea2023.org or dmdbsconf@yahoo.com
Submission URL :https://csea2023.org/submission/index.php
The document discusses future developments in cognitive-based knowledge acquisition systems using big data. It covers preparing students and the cognitive landscape for big data analytics through tools like concept maps and visualization. It also addresses challenges like determining where information comes from, whether humans or computers can best identify patterns in data, and whether autonomous systems will eventually replace human decision making.
4th International Conference on Data Science and Machine Learning (DSML 2023) gerogepatton
4th International Conference on Data Science and Machine Learning (DSML 2023) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Data Science and Machine Learning. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Data Science and Machine Learning.
Authors are solicited to contribute to the Conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the Computer Networks & Communications.
Una breve introduzione alla data science e al machine learning con un'enfasi sugli scenari applicativi, da quelli tradizionali a quelli più innovativi. La overview copre la definizione di base di data science, una overview del machine learning e esempi su scenari tradizionali, Recommender systems e Social Network Analysis, IoT e Deep Learning
Applying machine learning techniques to big data in the scholarly domainAngelo Salatino
Slides of the Lecture at the 5th International School on Applied Probability Theory,Communications Technologies & Data Science (APTCT-2020)
12 Nov 2020
This document discusses managing research data for open science based on the UK experience. It outlines key aspects of open science such as making research more open, global, collaborative and closer to society. The document discusses mandates for open research data from funding bodies in the UK and EU, including stipulations in Horizon 2020 and requirements from EPSRC. It defines what constitutes research data and examines challenges around research data management, including technology issues, people issues, policy issues and resources. The importance of data skills training for researchers and data professionals is also covered.
Submit Your Research Papers - International Conference on AI, Data Mining and...ijistjournal
International Conference on AI, Data Mining and Data Science (AIDD 2023) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence, Data mining, and Data Science. The Conference looks for significant contributions to all major fields of the AI, Data mining, and Data Science in theoretical and practical aspects.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:
Presentación Ciro Cattuto, ISI Foundation en VI Summit País Digital 2018PAÍS DIGITAL
Exposición “ Data Science for private and public good” de Ciro Cattuto, Scientific Director, ISI Foundation, en el marco del VI Summit País Digital 2018, realizado el 4 y 5 de septiembre en Santiago, Chile.
Linked Open Data about Springer Nature conferences. The story so farAliaksandr Birukou
Despite many efforts for making data about scholarly publications available on the Web of Data, lots of information about academic conferences is still contained in (at best) free-text format. When available in a structured format, these data would provide an essential input for the decisions researchers, libraries, publishers, funding and evaluation bodies take every day.
This talk will describe the project about having such data available as Linked Open Data (LOD) at lod.springer.com for around 10,000 computer science conferences. In addition, we will have a closer look at the lessons learnt from launching this portal and cover other Linked Data projects in Springer Nature. Finally, a novel semi-automated approach for classifying conference proceedings in Springer Nature will also be presented.
Submit Your Research Articles - International Conference on AI, Data Mining a...IJNSA Journal
International Conference on AI, Data Mining and Data Science (AIDD 2023) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence, Data mining, and Data Science. The Conference looks for significant contributions to all major fields of the AI, Data mining, and Data Science in theoretical and practical aspects.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:
Call for Research Articles - International Conference on AI, Data Mining and ...ijistjournal
International Conference on AI, Data Mining and Data Science (AIDD 2023) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence, Data mining, and Data Science. The Conference looks for significant contributions to all major fields of the AI, Data mining, and Data Science in theoretical and practical aspects.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:
Data Science is an interdisciplinary approach that combines computational science, statistics, and domain knowledge to extract meaningful insights from large and complex data. It aims to address challenges posed by the data revolution characterized by big data from diverse sources. There is no single agreed upon definition, but most definitions emphasize applying techniques from computer science, statistics, and the relevant domain area to discover patterns, make predictions, and support decision making from data. Key aspects include developing appropriate methodologies for knowledge discovery, forecasting and decisions using large and diverse data from sources like surveys, social media, sensors and more. The integration of domain knowledge representation with computational and statistical tools is seen as an important novelty that can enhance data analysis and interpretation.
A Comparative Study of Various Data Mining Techniques: Statistics, Decision T...Editor IJCATR
In this paper we focus on some techniques for solving data mining tasks such as: Statistics, Decision Trees and Neural
Networks. The new approach has succeed in defining some new criteria for the evaluation process, and it has obtained valuable results
based on what the technique is, the environment of using each techniques, the advantages and disadvantages of each technique, the
consequences of choosing any of these techniques to extract hidden predictive information from large databases, and the methods of
implementation of each technique. Finally, the paper has presented some valuable recommendations in this field.
The document provides an introduction to the concept of data mining. It discusses the evolution of data analysis techniques from empirical to computational to data-driven approaches. Data mining is presented as a natural evolution to analyze massive data sets and discover useful patterns. Key aspects of data mining covered include its functionality, types of data and knowledge that can be mined, major issues, and its relationship to other fields such as machine learning, statistics, and databases.
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Let me tell you what we see.
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[DSC Croatia 22] Writing scientific papers about data science projects - Mirjana Pejic Bach
1. Writing scientific papers
about data science
projects
Prof.Dr.Sc. Mirjana Pejić Bach
University of Zagreb, Faculty of Economics and Business
2. Education Roadmap
Faculty of Economics & Business –
Zagreb
Cybernetics & Finance (1993)
Faculty of Economics & Business –
Zagreb
MBA (1996)
Faculty of Economics & Business –
Zagreb
PhD (2003)
MIT Sloan School of Management
– System Dynamics
(1996)
3. Teaching Roadmap
Data mining / Data
science (2003-today)
System dynamics
(2010 –today)
Simulation games
(2007 - today)
Statistics
(1993-1996)
4. Sceintific Resarch Areas
Data mining / data
science
Technology acceptance
/ Digital divide
Statistical modelling
Editorial work /
Reviewer
13. Reasons for writing scientific articles
Increase knowledge - your own and others'
◦ Publication of results that are valuable
◦ Advancing science
Intellectual property protection - formal and informal
Expert reputation – establishing your position in a specific field
Scientific reputation - recognizability and citation
◦ Contact with a larger potential number of readers
◦ Scientific progress
◦ Doctoral study
◦ Scientific titles
◦ Teaching titles
14. How to write a scientific
paper in data science?
15. Pejić Bach, M. (2015). How to write and publish a scientific paper: A closer look to eastern European economics, business
and management journals. Business Systems Research: International journal of the Society for Advancing Innovation and
Research in Economy, 6(1), 93-103.
21. Search queries
Query Results
"data science" (Topic) 7,906 research papers
( "data science" OR "data mining" OR "big data" OR "artificial
intelligence" OR "AI" OR "statistical learning" OR "cluster
analysis" OR "decision trees" OR "artificial neural
networks" OR "ANN" OR "association rules" ) (Topic)
462,448 research papers
( "data science" OR "data mining" OR "big data" OR "artificial
intelligence" OR "AI" OR "statistical learning" OR "cluster
analysis" OR "decision trees" OR "artificial neural
networks" OR "ANN" OR "association rules" ) (Topic) and Highly
Cited Papers and 2021 (Publication Years)
734 research papers
24. Top 10 cited papers
1. Deep learning in neural networks: An overview
2. Mastering the game of Go with deep neural networks and tree search
3. Diagnostic Criteria for Multiple Sclerosis: 2010 Revisions to the McDonald Criteria
4. Representation Learning: A Review and New Perspectives
5. Dermatologist-level classification of skin cancer with deep neural networks
6. GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses
7. The Materials Project: A materials genome approach to accelerating materials innovation
8. Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications
9. Google Earth Engine: Planetary-scale geospatial analysis for everyone
10. Identification of human triple-negative breast cancer subtypes and preclinical models for
selection of targeted therapies
27. 0 1000 2000 3000 4000 5000 6000 7000 8000
REMOTE SENSING
JOURNAL OF INTELLIGENT FUZZY SYSTEMS
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND…
INFORMATION SCIENCES
APPLIED SOFT COMPUTING
ENERGIES
NEUROCOMPUTING
WEED TECHNOLOGY
IEEE INTERNATIONAL CONFERENCE ON BIG DATA
COMMUNICATIONS IN COMPUTER AND INFORMATION SCIENCE
NEURAL COMPUTING APPLICATIONS
SCIENTIFIC REPORTS
PROCEEDINGS OF SPIE
PROCEDIA COMPUTER SCIENCE
APPLIED SCIENCES BASEL
SENSORS
ANNALS OF NEUROLOGY
SUSTAINABILITY
PLOS ONE
ADVANCES IN INTELLIGENT SYSTEMS AND COMPUTING
EXPERT SYSTEMS WITH APPLICATIONS
LECTURE NOTES IN ARTIFICIAL INTELLIGENCE
ANNALS OF THORACIC SURGERY
IEEE ACCESS
LECTURE NOTES IN COMPUTER SCIENCE
# of publications
29. Methodology
Text mining is the process of exploring and analyzing large
amounts of unstructured text aided by software that can
identify concepts, patterns, topics, keywords and other
attributes in the data.
1st step – word and phrases extraction – Where is the
concern?
2nd step – topic extraction using cluster analysis – What
issues are in the focus?
30. Topic ( "data science" OR "data mining" OR "big
data" OR "artificial intelligence" OR "AI" OR "statistical
learning" OR "cluster analysis" OR "decision
trees" OR "artificial neural
networks" OR "ANN" OR "association rules" )
(462,448 papers)
Highly cited papers
(7906 papers)
Higly cited papers in 2021
(734 papers)
Results from Web of Science Core Collection
32. Example paper: Contreras-Valdes, A., Amezquita-Sanchez, J. P.,
Granados-Lieberman, D., & Valtierra-Rodriguez, M. (2020).
Predictive data mining techniques for fault diagnosis of electric
equipment: A review. Applied Sciences, 10(3), 950.
33. Example paper: Bandara, E., Ng, W. K., De Zoysa, K., Fernando, N., Tharaka, S.,
Maurakirinathan, P., & Jayasuriya, N. (2018, December). Mystiko—blockchain meets big data.
In 2018 IEEE international conference on big data (big data) (pp. 3024-3032). IEEE.
34. Example paper: Andrea, I., Chrysostomou, C., & Hadjichristofi, G. (2015,
July). Internet of Things: Security vulnerabilities and challenges. In 2015
IEEE symposium on computers and communication (ISCC) (pp. 180-187).
IEEE.
35. Example paper: Mookiah, M. R. K., Acharya, U. R., & Ng, E. Y. K. (2012).
Data mining technique for breast cancer detection in thermograms using
hybrid feature extraction strategy. Quantitative InfraRed Thermography
Journal, 9(2), 151-165.
36. Example paper: Brock, J. K. U., & Von Wangenheim, F. (2019). Demystifying AI: What digital transformation leaders
can teach you about realistic artificial intelligence. California Management Review, 61(4), 110-134.
37. Example paper: Bahrammirzaee, A. (2010). A comparative survey of artificial
intelligence applications in finance: artificial neural networks, expert system and
hybrid intelligent systems. Neural Computing and Applications, 19(8), 1165-1195.
38. Example paper: Müller, M., Salathé, M., & Kummervold, P. E. (2020). Covid-twitter-bert:
A natural language processing model to analyse covid-19 content on twitter. arXiv
preprint arXiv:2005.07503.
40. Course: Targeting the right journal /
conference
Select 2 to 3 journals / conferences for publication
the paper matches the topic of the journal
experience of other familiar authors that already published in the
journal
mission statements of the journals
members of the editorial bord
journal quality
Minimize rejections - quality of the paper = quality of the journal
The best papers – The best journals
Other worthy journals
preliminary research
narrow-topic articles
quick publication
a last-resource option if the paper gets rejected in highly-cited
journals
41. Avoid predatory journals and
conferences
What is meant by predatory Journal?
Predatory Journals take advantage of authors
by asking them to publish for a fee without
providing peer-review or editing services.
Because predatory publishers do not follow
the proper academic standards for publishing,
they usually offer a quick turnaround on
publishing a manuscript.
More info:
https://mdanderson.libanswers.com/faq/206
446
https://beallslist.net/
42. Conferences in Croatia & Slovenia
Central European Conference on Information and Intelligent Systems
• https://ceciis.foi.hr/
MIPRO – indexed in Scopus
◦ http://www.mipro.hr/
International Symposium on Operations Research in Slovenia – indexed in Scopus
◦ https://sor.fov.um.si/
International Conference on Operational Research (KOI)
◦ https://hdoi.hr/koi-2022/
45. The most reputable publishers
PAID FOR SUBSCRIPTION PUBLISHERS
Springer
Palgrave Macmillan
Routledge
Cambridge University Press
Elsevier
Nova Science Publishers
Edward Elgar
Information Age Publishing
Princeton University Press
University of California Press
Emerald
OPEN SOURCE PUBLISHERS
PlusOne
Sciendo
Mdpi
Frontiers
Most of paid-for-subscription publishers also publish open access journals and papers
47. Composition: IMRAD framework (1)
Different types of scientific papers
case studies
survey reports
theoretical papers
review papers
IMRAD framework
(1) Introduction (What problem was studied?)
(2) Methods (How was the problem studied?)
(3) Results (What are the results?)
(4) Discussion (What do the findings mean?)
Prof.dr.sc. Mirjana Pejić Bach
48. Title of the paper - understandable and informative, not too long
Abstract - background, purpose, results, methods and conclusion of the paper
Keywords - carefully select
Introduction section
1st paragraph - the current knowledge on the topic
2nd paragraph - direction toward the purpose of the paper
3rd paragraph - the purpose of the paper and it states briefly methodology that has been utilized in
the paper
4th paragraph - other sections of the paper
Convince the editor and the reader that the paper is worth of publishing and
reading.
Composition: IMRAD framework (2)
Prof.dr.sc. Mirjana Pejić Bach
49. Composition: IMRAD framework (3)
Literature review
elaborate the current knowledge
Methods section
the process author carried on in
order to finish the research,
quantitative and qualitative
research or combine together
Results section
present the facts revealed by the
research and not their
interpretation
Discussion section
hardest to write and its deficiencies
are the most often reason for the
papers being rejected
Summarize the findings of the research
– 1st paragraph
Compare the results being expected
from previous research or experience –
2nd paragraph
Propose practical implications of the
results – 3rd paragraph
Explain key limitations of the research –
4th paragraph
Suggest paths for the future research –
5ht paragraph
Prof.dr.sc. Mirjana Pejić Bach
52. Plagiarism Overview
Plagiarism is using someone else’s ideas or words without giving them proper credit. Plagiarism
can range from unintentional (forgetting to include a source in a bibliography) to intentional
(buying a paper online, using another writer’s ideas as your own to make your work sound
smarter). Beginning writers and expert writers alike can all plagiarize. Understand that
plagiarism is a serious charge in academia, but also in professional settings.
If you are...
a student — consequences can include failing grades on assignments or classes, academic
probation, and even expulsion.
a researcher — plagiarism can cause a loss of credibility, legal consequences, and other
professional consequences.
an employee in a corporate or similar setting — you can receive a reprimand or lose your job.
https://owl.purdue.edu/owl/avoiding_plagiarism/index.html
56. Writting scientific papers for beginners
Step 1:
◦ Find an article that serves as a prime example in terms of subject matter and structure there may be
similar topics
Step 2:
◦ Determine the working title of the article
Step 3: Create an article structure
Step 4: Write
◦ 1. introduction, 2. methods, 3. results, 4. discussion
Step 5: Write a summary and specify keywords
57.
58. How to Write a Paper for Publication Franklin L. Rosenfeldt , John T. Dowling,
Salvatore Pepe and Meryl J. Fullerton
60. • Read scientific papers
• Find example of paper on a similar topic in targeted
journal
• Examine how the paper is organized
• Make an outline for the content of the paper in the
form of a bullet list of the future paragraphs and even
sentences
• Start to write
Prof.dr.sc. Mirjana Pejić Bach
61. Messy process of
writting the paper
in scientific journal
PEJIC-BACH, M., BERTONCEL, T., MEŠKO, M., & KRSTIĆ, Ž. (2020). T EXT
MINING OF INDUSTRY 4.0 JOB ADVERTISEMENTS. INTERNATIONAL
JOURNAL OF INFORMATION MANAGEMENT, 50, 416-431.
62. Timeliness for journal writting
1.Shorter conference
papers
• 2-3 months
Longer conference
papers for top
conferences
• 6 months to 1 year
Local journals
• 6 months to 1 year
Top journals
• 1,5 to 3 years
63. Process (2,5 years)
COMPENTENCE:
1st phase – 3 months
◦ Topic of the paper – jobs in industry 4.0
◦ Data source – job advertisments
◦ Methodology – text mining; software – Provalis
2nd phase – 3 months
◦ Data collection
◦ Initial analysis
COURSE:
Journal selection – published similar papers
◦ Parallel process
COMPOSITION
1st draft of the paper following IMRAD
• 3 months
CONTENT
2nd draft of the paper
• 2 months
Final 1st version of the paper
• 6 months
Review process 3 rounds
• 1 year
64. The best way to learn about something
is to write about it!
Good luck!