Index of papers in Proc. ACL 2014 that mention
  • F-measure
Luo, Xiaoqiang and Pradhan, Sameer and Recasens, Marta and Hovy, Eduard
BLANC for Imperfect Response Mentions
and we propose to extend the coreference F-measure and non-coreference F-measure as follows.
BLANC for Imperfect Response Mentions
Coreference recall, precision and F-measure are changed to:
BLANC for Imperfect Response Mentions
Non-coreference recall, precision and F-measure are changed to:
Introduction
It calculates recall, precision and F-measure separately on coreference and non-coreference links in the usual way, and defines the overall recall, precision and F-measure as the mean of the respective measures for coreference and non-coreference links.
Original BLANC
BLANC-gold solves this problem by averaging the F-measure computed over coreference links and the F-measure over non-coreference links.
Original BLANC
Using the notations in Section 2, the recall, precision, and F-measure on coreference links are:
Original BLANC
Similarly, the recall, precision, and F-measure on non-coreference links are computed as:
F-measure is mentioned in 10 sentences in this paper.
Topics mentioned in this paper:
Zhou, Deyu and Chen, Liangyu and He, Yulan
Abstract
Experimental results show that the proposed model achieves 83% in F-measure , and outperforms the state-of-the-art baseline by over 7%.
Conclusions and Future Work
Experimental results show our proposed framework outperforms the state-of-the-art baseline by over 7% in F-measure .
Experiments
It is worth noting that the F-measure reported for the event phrase extraction is only 64% in the baseline approach (Ritter et al., 2012).
Experiments
Method Tuple Evaluated Precision Recall F-measure
Experiments
Method Tuple Evaluated Precision Recall F-measure
Introduction
We have conducted experiments on a Twitter corpus and the results show that our proposed approach outperforms TwiCal, the state-of-the-art open event extraction system, by 7.7% in F-measure .
F-measure is mentioned in 9 sentences in this paper.
Topics mentioned in this paper:
P, Deepak and Visweswariah, Karthik
Experimental Evaluation
leading to an F-measure of 53% for our initialization heuristic.
Experimental Evaluation
on various quality metrics, of which F-Measure is typically considered most important.
Experimental Evaluation
Our pure-LM13 setting (i.e., A = l) was seen to perform up to 6 F-Measure points better than the pure-TM14 setting (i.e., A = 0), whereas the uniform mix is seen to be able to harness both to give a 1.4 point (i.e., 2.2%) improvement over the pure-LM case.
F-measure is mentioned in 8 sentences in this paper.
Topics mentioned in this paper:
Liu, Kang and Xu, Liheng and Zhao, Jun
Experiments
Evaluation Metrics: We select precision(P), recall(R) and f-measure (F) as metrics.
Experiments
The experimental results are shown in Table 2, 3, 4 and 5, where the last column presents the average F-measure scores for multiple domains.
Experiments
Due to space limitation, we only show the F-measure of CR_WP on four domains.
F-measure is mentioned in 6 sentences in this paper.
Topics mentioned in this paper:
Sun, Le and Han, Xianpei
Introduction
Experimental results show that our method can achieve a 5.4% F-measure improvement over the traditional convolution tree kernel based method.
Introduction
The overall performance of CTK and FTK is shown in Table 1, the F-measure improvements over CTK are also shown inside the parentheses.
Introduction
FTK on the 7 major relation types and their F-measure improvement over CTK
F-measure is mentioned in 6 sentences in this paper.
Topics mentioned in this paper:
Xu, Liheng and Liu, Kang and Lai, Siwei and Zhao, Jun
Experiments
Evaluation Metrics: We evaluate the proposed method in terms of precision(P), recall(R) and F-measure (F).
Experiments
Figure 5 shows the performance under different N, where the F-Measure saturates when N equates to 40 and beyond.
Experiments
F-Measure
F-measure is mentioned in 6 sentences in this paper.
Topics mentioned in this paper:
Nagata, Ryo and Vilenius, Mikko and Whittaker, Edward
Evaluation
We measured correction performance by recall, precision, and F-measure .
Evaluation
The simple error case frame-based method achieves an F-measure of 0.189.
Evaluation
The hybrid methods achieve the best performances in F-measure .
F-measure is mentioned in 4 sentences in this paper.
Topics mentioned in this paper:
Chaturvedi, Snigdha and Goldwasser, Dan and Daumé III, Hal
Empirical Evaluation
Since the purpose of solving this problem is to identify the threads which should be brought to the notice of the instructors, we measure the performance of our models using F-measure of the positive class.
Empirical Evaluation
F-measure
Empirical Evaluation
6 shows 10-fold cross validation F-measure of the positive class for LR when different types of features are excluded from the full set.
F-measure is mentioned in 3 sentences in this paper.
Topics mentioned in this paper: