Importance

Loading Importance Indicators...

Abstract

Automatic classification is applied in two stages: classification and ranking. In the first stage, a categorization engine classifies incoming documents to topics. A document may be classified to a single topic or multiple topics or no topics. For each topic, a raw score is generated for a document and that raw score is used to determine whether the document should be at least preliminarily classified to the topic. In the second stage, for each document assigned to a topic (i.e., for each document-topic association) the categorization engine generates confidence scores expressing how confident the algorithm is in this assignment. The confidence score of the assigned document is compared to the topic's (configurable) threshold. If the confidence score is higher than this configurable threshold, the document is placed in the topic's Published list. If not, the document is placed in the topic's Proposed list, where it awaits approval by a knowledge management expert. By modifying a topic's threshold, a knowledge management expert can advantageously control the tradeoff between human oversight and control vs. time and human effort expended.

Loading the Abstract Image...

First Claim