Knowledge Discovery is an interdisciplinary area focusing upon methodologies for identifying valid, novel, potentially useful and meaningful patterns from data, often based on underlying large data sets. A major aspect of Knowledge Discovery is data mining, i.e. applying data analysis and discovery algorithms that produce a particular enumeration of patterns (or models) over the data. Knowledge Discovery also includes the evaluation of patterns and identification of which add to knowledge.
Information retrieval (IR) is concerned with gathering relevant information from unstructured and semantically fuzzy data in texts and other media, searching for information within documents and for metadata about documents, as well as searching relational databases and the Web. Automation of information retrieval enables the reduction of what has been called "information overload".
Information retrieval can be combined with knowledge discovery to create software tools that empower users of decision support systems to better understand and use the knowledge underlying large data sets.
BioInformatics & Pattern Discovery
Business Intelligence Applications
Clustering and Classification Methods
Collaborative Filtering
Concept Mining
Context Discovery
Data Analytics
Data Mining in Electronic Commerce
Data Reduction and Quality Assessment
Foundations of Knowledge Discovery in Databases
Information Extraction
Interactive and Online Data Mining
Machine Learning
Mining Multimedia Data
Mining Text and Semi-structured Data
Pre-processing and Post-processing for Data Mining
Process Mining
Software Development
Structured Data Analysis and Statistical Methods
User Profiling and Recommender Systems
Visual Data Mining and Data Visualization
Web Mining
11月09日
2016
11月11日
2016
初稿截稿日期
注册截止日期
2018年09月18日 西班牙
第十届国际知识发现与信息检索会议2017年11月01日 葡萄牙 Funchal,Portugal
2017第九届知识发现与信息检索国际会议2015年11月12日 葡萄牙
第七届知识发现与信息检索国际会议2013年09月19日 葡萄牙
第五届国际知识发现与信息检索会议
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