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Chapter and Conference Paper
Matrices, Compression, Learning Curves: Formulation, and the GroupNteach Algorithms
Suppose you are a teacher, and have to convey a set of object-property pairs (‘lions eat meat’). A good teacher will convey a lot of information, with little effort on the student side. What is the best and mo...
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Chapter and Conference Paper
Mining Videos from the Web for Electronic Textbooks
We propose a system for mining videos from the web for supplementing the content of electronic textbooks in order to enhance their utility. Textbooks are generally organized into sections such that each sectio...
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Chapter and Conference Paper
Enriching Education through Data Mining
Education is acknowledged to be the primary vehicle for improving the economic well-being of people [1,6]. Textbooks have a direct bearing on the quality of education imparted to the students as they are the p...
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Chapter and Conference Paper
Enriching Education through Data Mining
Education is acknowledged to be the primary vehicle for improving the economic well-being of people [1,6]. Textbooks have a direct bearing on the quality of education imparted to the students as they are the p...
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Article
Automatic Subspace Clustering of High Dimensional Data
Data mining applications place special requirements on clustering algorithms including: the ability to find clusters embedded in subspaces of high dimensional data, scalability, end-user comprehensibility of t...
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Chapter and Conference Paper
Mining Information Extraction Rules from Datasheets Without Linguistic Parsing
In the context of the Pangea project at IBM, we needed to design an information extraction module in order to extract some information from datasheets. Contrary to several information extraction systems based ...
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Chapter and Conference Paper
Data Privacy
There is increasing need to build information systems that protect the privacy and ownership of data without impeding the flow of information. We will present some of our current work to demonstrate the techni...
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Chapter and Conference Paper
Data Privacy
There is increasing need to build information systems that protect the privacy and ownership of data without impeding the flow of information. We will present some of our current work to demonstrate the techni...
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Article
Constraint-Based Rule Mining in Large, Dense Databases
Constraint-based rule miners find all rules in a given data-set meeting user-specified constraints such as minimum support and confidence. We describe a new algorithm that directly exploits all user-specified ...
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Article
Integrating Association Rule Mining with Relational Database Systems: Alternatives and Implications
Data mining on large data warehouses is becoming increasingly important. In support of this trend, we consider a spectrum of architectural alternatives for coupling mining with database systems. These alternat...
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Chapter and Conference Paper
Mining process models from workflow logs
Modern enterprises increasingly use the workflow paradigm to prescribe how business processes should be performed. Processes are typically modeled as annotated activity graphs. We present an approach for a sys...
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Chapter and Conference Paper
Discovery-driven exploration of OLAP data cubes
Analysts predominantly use OLAP data cubes to identify regions of anomalies that may represent problem areas or new opportunities. The current OLAP systems support hypothesis-driven exploration of data cubes t...
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Chapter and Conference Paper
SLIQ: A fast scalable classifier for data mining
Classification is an important problem in the emerging field of data mining. Although classification has been studied extensively in the past, most of the classification algorithms are designed only for memory...
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Chapter and Conference Paper
Mining sequential patterns: Generalizations and performance improvements
The problem of mining sequential patterns was recently introduced in [3]. We are given a database of sequences, where each sequence is a list of transactions ordered by transaction-time, and each transaction i...
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Chapter and Conference Paper
Type derivation using the projection operation
We present techniques for deriving types from existing objectoriented types using the relational algebraic projection operation and for inferring the methods that are applicable to these types. Such type deriv...