Related Work | We operationalize these notions using a scoring function that quantifies the compatibility between arbitrary cluster pairs. |
Split-Merge Role Induction | Besides being inefficient, it requires a scoring function with comparable scores for arbitrary pairs of clusters. |
Split-Merge Role Induction | After each completion of the inner loop, the thresholds contained in the scoring function (discussed below) are adjusted and this is repeated until some termination criterion is met (discussed in Section 5.2.3). |
Split-Merge Role Induction | 5.2.2 Scoring Function |
Abstract | We propose a context-sensitive topical PageRank method for keyword ranking and a probabilistic scoring function that considers both relevance and interestingness of keyphrases for keyphrase ranking. |
Experiments | We have proposed a context-sensitive topical PageRank method (cTPR) for the first step of keyword ranking, and a probabilistic scoring function for the third step of keyphrase ranking. |
Method | While a standard method is to simply aggregate the scores of keywords inside a candidate keyphrase as the score for the keyphrase, here we propose a different probabilistic scoring function . |
Method | tion (8) into Equation (3) and obtain the following scoring function for ranking: |
Method | Our preliminary experiments with Equation (9) show that this scoring function usually ranks longer keyphrases higher than shorter ones. |