| Id |
Subject |
Object |
Predicate |
Lexical cue |
| T588 |
0-43 |
Sentence |
denotes |
Evaluation Measures Equations Description |
| T589 |
44-238 |
Sentence |
denotes |
Precision Precision=1n ∑j|Rj ∩Mj ||Rj| (3) This is defined as the ratio of the total number of items appearing in both Rj and Mj to the total number of Rj [66]. n is the total number of users. |
| T590 |
239-317 |
Sentence |
denotes |
A higher value for the Precision means better performance and higher accuracy. |
| T591 |
318-482 |
Sentence |
denotes |
Recall Recall=1n ∑j|Rj ∩Mj ||Mj| (4) The Recall measure is defined as the ratio of the total number of items appearing in both Rj and Mj to the number of Mj [66]. |
| T592 |
483-623 |
Sentence |
denotes |
Similarly, to the Precision measure, a higher value for Recall means a better performance and higher accuracy for the recommender algorithm. |
| T593 |
624-789 |
Sentence |
denotes |
F-Score F Score = 2*(Recall * Precision)/(Recall + Precision) (5) The F-score combines both the precision and recall into one metric that captures both properties. |
| T594 |
790-858 |
Sentence |
denotes |
In other words, it is the weighted average for precision and recall. |
| T595 |
859-910 |
Sentence |
denotes |
This metric gives an overview of the model results. |
