Descriptor
| Automatic Indexing | 5 |
| Mathematical Models | 5 |
| Probability | 5 |
| Classification | 3 |
| Cluster Grouping | 3 |
| Statistical Analysis | 3 |
| Algorithms | 2 |
| Bayesian Statistics | 2 |
| Databases | 2 |
| Documentation | 2 |
| Information Retrieval | 2 |
| More ▼ | |
Author
| White, Lee J. | 2 |
| Bookstein, Abraham | 1 |
| Harding, P. | 1 |
| Harter, Stephen P. | 1 |
| Kar, B. Gautam | 1 |
| Robertson, S. E. | 1 |
| Swanson, Don R. | 1 |
Publication Type
| Reports - Research | 3 |
| Journal Articles | 1 |
Education Level
Audience
| Researchers | 1 |
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewedHarter, Stephen P. – Journal of the American Society for Information Science, 1975
Confirms previously published research in concluding that specialty words tend to possess frequency distributions which cannot be described by a single Poisson distribution. (Author/PF)
Descriptors: Automatic Indexing, Indexing, Keywords, Mathematical Models
Peer reviewedBookstein, Abraham; Swanson, Don R. – Journal of the American Society for Information Science, 1974
Descriptors: Automatic Indexing, Cluster Grouping, Indexes, Information Retrieval
Peer reviewedRobertson, S. E.; Harding, P. – Journal of Documentation, 1984
Presents adaptation of a probabilistic theoretical model previously used in relevance feedback for use in automatic indexing of documents (in the sense of imitating) human indexers. Methods for model application are proposed, independence assumptions used in the model are interpreted, and the probability of a dependence model is discussed.…
Descriptors: Automatic Indexing, Classification, Information Retrieval, Mathematical Models
PDF pending restorationWhite, Lee J.; And Others – 1975
The major advantage of sequential classification, a technique for automatically classifying documents into previously selected categories, is that the entire document need not be processed before it is classified. This method assumes the availability of a priori categories, a selection of keywords representative of these categories, and the a…
Descriptors: Algorithms, Automatic Indexing, Bayesian Statistics, Classification
Kar, B. Gautam; White, Lee J. – 1975
The feasibility of using a distance measure, called the Bayesian distance, for automatic sequential document classification was studied. Results indicate that, by observing the variation of this distance measure as keywords are extracted sequentially from a document, the occurrence of noisy keywords may be detected. This property of the distance…
Descriptors: Algorithms, Automatic Indexing, Bayesian Statistics, Classification


