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| Content Provider | ACM Digital Library |
|---|---|
| Author | Rice, Sally Roddick, John F. |
| Abstract | Despite significant progress, determining the interestingness of a rule remains a difficult problem. This short paper investigates the lessons that may be learned from analysing the (largely manual) selection of interesting statistics for cricket (or any other data rich sport) by experts. In particular, the effect of thresholds on the interestingness of rules describing events in the sporting arena is discussed. The concept of anticipation is shown also to be critical in this selection and to vary the level of interest in events that may contribute to the achievement of a threshold value during a match, thus adding a temporal dimension to interestingness. This temporal aspect can be best modelled on the single-past-branching-future model of time. As a result of this investigation, a few new general ideas are discussed that add to the research in this area. Significantly, some of the new criteria are implicitly temporal in that they rely on a model of behaviour over time. The applicability of threshold values for detecting uncharacteristically poor performances are canvassed as areas of interest yet to be explored. |
| Starting Page | 1 |
| Ending Page | 5 |
| Page Count | 5 |
| File Format | |
| ISSN | 19310145 19310153 |
| DOI | 10.1145/507533.507535 |
| Journal | ACM SIGKDD Explorations Newsletter (SKDD) |
| Volume Number | 3 |
| Issue Number | 1 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2000-06-01 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Temporal data mining Cricket statistics Knowledge discovery Interestingness criteria |
| Content Type | Text |
| Resource Type | Article |
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