TY - GEN
T1 - Determining the fitness of a document model by using conflict instances
AU - Chen, Ding-Yi
AU - Li, Xue
AU - Dong, Zhao Yang
AU - Chen, Xia
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2005
Y1 - 2005
N2 - Documents cannot be automatically classified unless they have been represented as a collection of computable features. A model is a representation of a document with computable features. However, a model may not be sufficient to express a document, especially when two documents have the same features, they might not be necessarily classified into the same category. We propose a method for determining the fitness of a document model by using conflict instances. Conflict instances are instances with exactly same features, but with different category labels given by human expert in an interactive document labelling process for training of the classifier. In our paper, we do not treat conflict instances as noises, but as the evidences that can reveal a distribution of positive instances. We develop an approach to the representation of this distribution information as a hy-perplane, namely distribution hyperplane. Then the fitness problem becomes a problem of computing the distribution hyperplane. Besides determining the fitness of a model, distribution hyperplane can also be used for: 1) acting as classifier itself; and 2) being a membership function of fuzzy sets. In this paper, we also propose the selection criteria of effectiveness measuring for a model in a process of fitness computations. © 2005, Australian Computer Society, Inc.
AB - Documents cannot be automatically classified unless they have been represented as a collection of computable features. A model is a representation of a document with computable features. However, a model may not be sufficient to express a document, especially when two documents have the same features, they might not be necessarily classified into the same category. We propose a method for determining the fitness of a document model by using conflict instances. Conflict instances are instances with exactly same features, but with different category labels given by human expert in an interactive document labelling process for training of the classifier. In our paper, we do not treat conflict instances as noises, but as the evidences that can reveal a distribution of positive instances. We develop an approach to the representation of this distribution information as a hy-perplane, namely distribution hyperplane. Then the fitness problem becomes a problem of computing the distribution hyperplane. Besides determining the fitness of a model, distribution hyperplane can also be used for: 1) acting as classifier itself; and 2) being a membership function of fuzzy sets. In this paper, we also propose the selection criteria of effectiveness measuring for a model in a process of fitness computations. © 2005, Australian Computer Society, Inc.
KW - Conflict instances
KW - Distribution hyperplane
KW - Document classification
KW - Document model
KW - Document model fitness
UR - https://www.scopus.com/pages/publications/84873325171
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84873325171&origin=recordpage
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 192068221
SN - 9781920682217
VL - 39
T3 - Conferences in Research and Practice in Information Technology Series
SP - 125
EP - 133
BT - Database Technologies 2005 - Sixteenth Australasian Database Conference, ADC 2005
T2 - 16th Australasian Database Conference, ADC 2005
Y2 - 31 January 2005 through 1 February 2005
ER -