Principles of database and knowledge-base systems, Vol. I
Principles of database and knowledge-base systems, Vol. I
The Unified Modeling Language reference manual
The Unified Modeling Language reference manual
Modern Information Retrieval
Entity-Relationship Modeling: Foundations of Database Technology
Entity-Relationship Modeling: Foundations of Database Technology
IEEE Intelligent Systems
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Selecting the right interestingness measure for association patterns
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Finding Interesting Associations without Support Pruning
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Implicit link analysis for small web search
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Data quality and data cleaning: an overview
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Unsupervised Link Discovery in Multi-relational Data via Rarity Analysis
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Interestingness of frequent itemsets using Bayesian networks as background knowledge
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Artificial Intelligence in Medicine
Information retrieval with a simplified conceptual graph-like representation
MICAI'10 Proceedings of the 9th Mexican international conference on Advances in artificial intelligence: Part I
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Many analysis of data proceed by building a graph out of the data set and then using social network theory and similar tools on the result. However, there is no theory concerning the construction of the graph itself, even though this is a very important process. In this paper, we attempt to provide a framework in which the graph building process is formalized and studied. We show the parameters (choices) involved in constructing a graph from raw data, and propose some new ways to combine and analyze the data. We also argue the importance of this approach in several domain applications, including criminal/terrorist investigations.