Domain driven tree mining of semi-structured mental health information

QR Code

Domain driven tree mining of semi-structured mental health information

The World Health Organization predicted that depression would be the world's leading cause of disability by 2020. This is calling for urgent interventions. As most mental illnesses are caused by a number of genetic and environmental factors and many different types of mental illness exist, the...

Full description

Bibliographic Details
Main Authors:	Hadzic, Fedja, Dillon, Tharam S., Hadzic, Maja
Other Authors:	Longbing Cao
Format:	Book Chapter
Published:	Springer 2009
Online Access:	http://www.springerlink.com/content/978-0-387-79419-8 http://hdl.handle.net/20.500.11937/28749

Similar Items

Tree mining in mental health domain
by: Hadzic, Maja, et al.
Published: (2008)

Mining of health information from ontologies
by: Hadzic, Maja, et al.
Published: (2008)

Thinking PubMed: an innovative system for mental health domain
by: Hadzic, Maja, et al.
Published: (2008)

Application of tree mining to matching of knowledge structures of decision tree type
by: Hadzic, Fedja, et al.
Published: (2007)

Synergy on ontology and data mining: increasing value of the mental health
by: Hadzic, Maja, et al.
Published: (2008)

Conjoint data mining of structured and semi-structured data
by: Pan, Qi, et al.
Published: (2008)

State of the art of data mining of tree structured information
by: Tan, H., et al.
Published: (2008)

Mining of patient data: towards better treatment strategies for depression
by: Hadzic, Maja, et al.
Published: (2010)

Application of digital ecosystems in health domain
by: Hadzic, Maja, et al.
Published: (2008)

Tree mining application to matching of hetereogeneous knowledge
by: Hadzic, Fedja, et al.
Published: (2007)

Role of Multi-Agents System in Creation of Collaborative Environments within Mental Health Domain
by: Hadzic, Maja, et al.
Published: (2010)

Web semantics for intelligent and dynamic information retrieval illustrated within the mental health domain
by: Hadzic, Maja, et al.
Published: (2008)

Mining of Data with Complex Structures
by: Hadzic, Fedja, et al.
Published: (2011)

Human-like rule optimization for continuous domains
by: Hadzic, Fedja, et al.
Published: (2008)

Towards the mental health ontology
by: Hadzic, Maja, et al.
Published: (2008)

Three fold system (3FS) for mental health domain
by: Hadzic, Maja, et al.
Published: (2007)

Alternative approach to tree-structured web log representation and mining
by: Hadzic, Fedja, et al.
Published: (2011)

Incorporating qualitative information for credit risk assessment through frequent subtree mining for XML
by: Ikasari, Novita, et al.
Published: (2011)

Using the symmetrical Tau criterion for feature selection decision tree and neural network learning
by: Hadzic, Fedja, et al.
Published: (2006)

Human stress ontology: multiple applications and implications of an ontology framework in the mental health domain
by: Khoozani, Ehsan, et al.
Published: (2010)

Knowledge analyisis with tree patterns
by: Hadzic, Fedja, et al.
Published: (2008)

A structure preserving flat data format representation for tree-structured data
by: Hadzic, Fedja
Published: (2012)

MB3-Miner: Efficient mining eMBedded subTREEs using tree model guided candidate generation
by: Chang, Elizabeth, et al.
Published: (2005)

Application of tree-structured data mining for analysis of process logs in XML format
by: Bui, Dang, et al.
Published: (2012)

A framework for application of tree-structured data mining to process log analysis
by: Bui, Dang, et al.
Published: (2012)

Mining unordered distance-constrained embedded subtrees
by: Hadzic, Fedja, et al.
Published: (2008)

Model guided algorithm for mining unordered embedded subtrees
by: Hadzic, Fedja, et al.
Published: (2010)

Spirituality and mental health: current research and future directions
by: Hadzic, Maja
Published: (2011)

U3 - mining unordered embedded subtrees using TMG candidate generation
by: Hadzic, Fedja, et al.
Published: (2008)

Tree model guided candidate generation for mining frequent subtrees from XML
by: Tan, Henry, et al.
Published: (2008)

Ascertaining data mining rules using statistical approaches
by: Mohd Shaharanee, I., et al.
Published: (2009)

Application of Digital Ecosystem Design Methodology Within the Health Domain
by: Hadzic, Maja, et al.
Published: (2010)

An agent-based data mining system for ontology evolution
by: Hadzic, Maja, et al.
Published: (2009)

Razor: Mining distance-constrained embedded subtrees
by: Tan, H., et al.
Published: (2006)

SEQUEST: Mining frequent subsequences using DMA strips
by: Tan, H., et al.
Published: (2006)

Ontology support for biomedical information resources
by: Dillon, Tharam S., et al.
Published: (2008)

Implications of frequent subtree mining using hybrid support definitions
by: Hadzic, Fedja, et al.
Published: (2007)

Mining Induced/Embedded Subtrees using the Level of Embedding Constraint
by: Tan, H., et al.
Published: (2012)

Rule optimizing technique motivated by human concept formation
by: Hadzic, Fedja, et al.
Published: (2008)

CSOM: self-organizing map for continuous data
by: Hadzic, Fedja, et al.
Published: (2005)