 |
 |
 |
 |
 |
 |
||
 |
 |
 |
 |
 |
| 2 | 1/1 | 返回列表 |
| 查看: 3029 | 回復: 30 | ||
| 【懸賞金幣】回答本帖問題，作者空空如也0將贈送您 50 個金幣 | ||
| 當前只顯示滿足指定條件的回帖，點擊這里查看本話題的所有回帖 | ||
[求助]
給了一個月的修訂時間，我10天就改好了。我要不要等到一個月后再投？ 已有6人參與
|
||
|
審稿意見： Reviewer #1: I understand that AL-based approach needs both "initial training set" and "the newly added samples" in order to select most representative samples. However, there are two questions. First, what do you mean representative samples? Does it mean a set of samples which covers both valid and invalid links? Second, it seems that in the Algorithm 1, active learning relies on the termination condition to ensure the representativeness of the samples. If I am correct, the termination condition used in the paper (i.e., the number of labeled samples reaches a preset value) does not make any sense. A better termination condition could be the labeled samples shall contains at least 1 valid link and 1 invalid link. Reviewer #2: Tracking the relation between artifacts in software project is important. Generally, it is human intensive task to construct the traceability links. Traditional information retrieve techniques has been employed to automatic analyze and recover traceability links. Even machine learning approaches as adopted to train an effective predictive model for traceability link recovery. It requires humans to label traceability links. This paper presents a TLR approach based on active learning. Evaluation experiments were conducted on seven commonly used traceability datasets. It was compared with an IR-based approach and a current machine learning approach. The experiment shows that AL-based approach outperforms the other two approaches in terms of F-score. Concerns 1、 Page1, "(hereafter called AL-based approach)" is repeated in the abstract and introduction. 2、 Page 1, section 1, left column, last line, "traceability" means "traceability relationships" or "traceability links"? 3、 Page 2, left column, "TSL-based approach is that how to select traceability links for labeling to generate traceability information."=》that 4、 Page 3, Section 3, Step1: (1)" randomly selecting a small number of samples for labeling to initialize Dt", =>"randomly labeling a small number of samples to initialize Dt " 5、 Page 3, Section 3, Step1: (3) "selecting an unlabeled sample from the unlabeled sample set based on sample selection strategy and requesting experts to label the sample"=> The authors need to define the D and Dl here. Regarding to the context, the Dt and Dl seem equivalent, why use different symbol? 6、 Page 3, Section 3, Step 4, This paper chose Random Forest as the classification algorithm. However, the authors only claimed that "The reason for choosing Random Forest is because it has been shown to be accurate and robust". It would be better to explain why random forest is more suitable for the task. 7、 Page 4, Algorithm1 needs to be reconstructed. It would be much better to define input and output, as well as all the variables used in the algorithm. 8、 Section 4. It would be much better to move Experimental metric at the beginning of section 4. Authors use the F-score before its definition. 9、 The format of refences should be standardized, especially, the names and abbreviations of journals and conferences. |
回復此樓» 猜你喜歡
11408軟件工程求調劑
已經有3人回復
-
一志愿211 初試270分 求調劑
已經有8人回復
-
300求調劑，材料科學英一數二
已經有6人回復
-
學碩274求調劑
已經有9人回復
-
本科雙非材料，跨考一志愿華電085801電氣，283求調劑，任何專業(yè)都可以
已經有7人回復
-
各位老師好，我的一志愿為北京科技大學085601材料專碩
已經有3人回復
-
317分 一志愿南理工材料工程 本科湖工大 求調劑
已經有7人回復
-
081200-11408-276學碩求調劑
已經有5人回復
-
316求調劑
已經有7人回復
-
322求調劑
已經有7人回復
感謝參與，應助指數 +1
|
本帖內容被屏蔽 |
31樓2019-08-01 05:43:21
相關版塊跳轉
我要訂閱樓主 空空如也0 的主題更新
| 2 | 1/1 | 返回列表 |
| 最具人氣熱帖推薦 [查看全部] | 作者 | 回/看 | 最后發(fā)表 | |
|---|---|---|---|---|
|
[考研] 085701求調劑初試286分 +4 | secret0328 2026-03-28 | 4/200 |
|
|---|---|---|---|---|
|
[考研] 315求調劑 +4 | akie... 2026-03-28 | 5/250 |
|
|
|
[考研] 321求調劑 +6 | 璞玉~~ 2026-03-25 | 7/350 |
|
|
|
[考研] 本科新能源科學與工程，一志愿華理能動285求調劑 +3 | AZMK 2026-03-27 | 5/250 |
|
|
|
[考研] 一志愿太原理工安全工程300分，求調劑 +4 | 0857求調劑. 2026-03-24 | 5/250 |
|
|
|
[考研] 材料277求調劑 +7 | min3 2026-03-24 | 7/350 |
|
|
|
[考研] 286求調劑 +4 | 丟掉懶惰 2026-03-27 | 7/350 |
|
|
|
[考研] 085404求調劑，總分309，本科經歷較為豐富 +4 | 來財aa 2026-03-25 | 4/200 |
|
|
|
[考研] 316求調劑 +5 | Pigcasso 2026-03-24 | 5/250 |
|
|
|
[考研] 317求調劑 +7 | 蛋黃咸肉粽 2026-03-26 | 7/350 |
|
|
|
[考研] 336材料求調劑 +7 | 陳瀅瑩 2026-03-26 | 9/450 |
|
|
|
[考研] 求調劑 一志愿 本科 北科大 化學 343 +6 | 13831862839 2026-03-24 | 7/350 |
|
|
|
[考研]
材料調劑
 5+4
|
想要一壺桃花水 2026-03-25 | 10/500 |
|
|
|
[考研] 總分322求生物學/生化與分子/生物信息學相關調劑 +5 | 星沉uu 2026-03-26 | 6/300 |
|
|
|
[考研] 生物學 296 求調劑 +4 | 朵朵- 2026-03-26 | 6/300 |
|
|
|
[考研] 一志愿中南大學化學學碩0703總分337求調劑 +7 | niko- 2026-03-22 | 7/350 |
|
|
|
[有機交流]
 有機合成求助
20+3
|
FENGSHUJEI 2026-03-23 | 5/250 |
|
|
|
[基金申請] 請教下大家 2026年國家基金申請是雙盲審嗎？ +3 | lishucheng1 2026-03-22 | 5/250 |
|
|
|
[考研] 361求調劑 +3 | Glack 2026-03-22 | 3/150 |
|
|
|
[考研] 269求調劑 +4 | 我想讀研11 2026-03-23 | 4/200 |
|