Hybrid Conferencee

International Conference on Information Science and Data Mining (ICISDM - 26)

30th - 1st July 2026 | New York, USA
Sample Abstract
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Conference Brochure
Sample Full Paper
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Conference Notifications:

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Call for Papers Extended:
"The deadline for full paper submissions has been extended for the Research Plus International Conference in New York. Submit your research by today to participate in one of the top conferences."
Certificate of Presentation:
"Present your research and receive a Certificate of Presentation to recognise your valuable contribution to the conference."
Abstract Submissions Open:
"Abstract submissions for the New York event are now open! Don’t miss the chance to present your research. Submit now."
Networking with Global Experts:
"Engage with researchers and professionals from around the world at the New York conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in New York, featuring global leaders and innovators sharing their knowledge."
Best Paper & Best Paper Presentation Award:
"Submit your paper and stand a chance to win the Best Paper Presentation Award. The winner will be recognized at the conference in New York."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICISDM aims to explore emerging trends and future directions in research and innovation. It provides a collaborative platform for researchers and professionals to share ideas that shape the future of their respective domains.

The conference highlights advancements in Information Science, encouraging innovative, solution-oriented research that addresses global challenges and technological evolution.

Authors are invited to submit papers addressing, but not limited to, the following areas:

01
Data mining techniques and applications
02
Information retrieval in big data
03
Machine learning for data analysis
04
Data visualization methods and tools
05
Ethics in data mining practices
06
Social media data mining strategies
07
Predictive analytics in information science
08
Data mining for healthcare applications
09
Text mining and natural language processing
10
Data privacy and security concerns
11
Real-time data processing techniques
12
Data mining in educational contexts
13
Sentiment analysis in social media
14
Data mining for financial forecasting
15
Challenges in big data analytics
16
Data quality assessment methods
17
Cloud computing for data mining
18
Interdisciplinary approaches to data mining
19
Data mining in IoT environments
20
Future trends in information science