 |
 |
 |
 |
 |
 |
||
 |
 |
 |
 |
 |
| 5 | 3/1 | 返回列表 |
| 查看: 3034 | 回復(fù): 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(dāng)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(fù)此樓» 猜你喜歡
考研調(diào)劑
已經(jīng)有3人回復(fù)
-
317分 一志愿南理工材料工程 本科湖工大 求調(diào)劑
已經(jīng)有9人回復(fù)
-
297求調(diào)劑
已經(jīng)有10人回復(fù)
-
一志愿武漢理工，總分321，英一數(shù)二，求老師收留。
已經(jīng)有10人回復(fù)
-
343求調(diào)劑
已經(jīng)有5人回復(fù)
-
085601材料工程找調(diào)劑
已經(jīng)有7人回復(fù)
-
求調(diào)劑，一志愿 南京航空航天大學(xué) ，080500材料科學(xué)與工程學(xué)碩，總分289分
已經(jīng)有6人回復(fù)
-
一志愿南航 335分 | 0856 | GPA 4.07 | 有科研經(jīng)歷
已經(jīng)有5人回復(fù)
-
340求調(diào)劑
已經(jīng)有5人回復(fù)
-
一志愿北化求調(diào)劑
已經(jīng)有4人回復(fù)
￥笑傲江湖￥
鐵桿木蟲 (職業(yè)作家)
劍橋第一人
- 應(yīng)助: 35 (小學(xué)生)
- 金幣: 7988.4
- 散金: 2847
- 紅花: 26
- 沙發(fā): 2
- 帖子: 3557
- 在線: 883.4小時
- 蟲號: 3946131
- 注冊: 2015-06-29
- 性別: GG
- 專業(yè): 基礎(chǔ)物理學(xué)
25樓2019-07-31 15:20:06
2樓2019-07-30 17:29:30
國際科學(xué)編輯 
鐵桿木蟲 (知名作家)
- 應(yīng)助: 1532 (講師)
- 金幣: 3627.6
- 散金: 615
- 紅花: 275
- 沙發(fā): 3
- 帖子: 7972
- 在線: 146.9小時
- 蟲號: 4407167
- 注冊: 2016-02-16
- 性別: GG
- 專業(yè): 病原微生物變異與耐藥
【答案】應(yīng)助回帖
★
感謝參與，應(yīng)助指數(shù) +1
paperhunter: 金幣+1, 鼓勵交流 2019-07-31 11:48:46
感謝參與，應(yīng)助指數(shù) +1
paperhunter: 金幣+1, 鼓勵交流 2019-07-31 11:48:46
|
完全沒有必要，覺得改好了就返回吧 發(fā)自小木蟲IOS客戶端 |
3樓2019-07-30 17:31:43
jokage
新蟲 (著名寫手)
- 應(yīng)助: 1 (幼兒園)
- 金幣: 1167.2
- 散金: 4647
- 紅花: 22
- 帖子: 2043
- 在線: 437.1小時
- 蟲號: 2325646
- 注冊: 2013-03-07
- 性別: GG
- 專業(yè): 天文技術(shù)和方法
4樓2019-07-30 17:34:01
| 最具人氣熱帖推薦 [查看全部] | 作者 | 回/看 | 最后發(fā)表 | |
|---|---|---|---|---|
|
[考研] 340求調(diào)劑 +5 | Amber00 2026-03-26 | 5/250 |
|
|---|---|---|---|---|
|
|
[考研] 332求調(diào)劑 +8 | 蕉蕉123 2026-03-28 | 8/400 |
|
|
[考研] 0856材料化工調(diào)劑 總分330 +14 | zhubinhao 2026-03-27 | 14/700 |
|
|
|
[考研] 數(shù)一英一271專碩（085401）求調(diào)劑，可跨 +7 | 前行必有光 2026-03-28 | 8/400 |
|
|
|
[考研] 085602 化工專碩 338分 求調(diào)劑 +12 | 路癡小琪 2026-03-27 | 12/600 |
|
|
|
[考研] 復(fù)試調(diào)劑 +3 | raojunqi0129 2026-03-28 | 3/150 |
|
|
|
[考研] 一志愿中南大學(xué)化學(xué)0703總分337求調(diào)劑 +5 | niko- 2026-03-27 | 5/250 |
|
|
|
[考研] 304求調(diào)劑 +6 | 曼殊2266 2026-03-27 | 6/300 |
|
|
|
[考研] 317求調(diào)劑 +6 | 十閑wx 2026-03-24 | 6/300 |
|
|
|
[考研] 266分，求材料冶金能源化工等調(diào)劑 +7 | 哇呼哼呼哼 2026-03-27 | 9/450 |
|
|
|
[考研] 一志愿南京航空航天大學(xué)材料學(xué)碩求調(diào)劑 +3 | @taotao 2026-03-28 | 3/150 |
|
|
|
[材料工程] 一志愿C9材料與化工專業(yè)總分300求調(diào)劑 +8 | 曼111 2026-03-24 | 9/450 |
|
|
|
[考研] 086502化學(xué)工程342求調(diào)劑 +6 | 阿姨復(fù)古不過 2026-03-27 | 6/300 |
|
|
|
[考研] 265求調(diào)劑 +8 | 小木蟲085600 2026-03-27 | 8/400 |
|
|
|
[論文投稿] Journal of Mechanical Science and Technology +3 | Russ_ss 2026-03-25 | 5/250 |
|
|
|
[考研] 求調(diào)劑，一志愿 南京航空航天大學(xué)大學(xué) ，080500材料科學(xué)與工程學(xué)碩 +4 | @taotao 2026-03-26 | 5/250 |
|
|
|
[考研] 334分 一志愿武理 材料求調(diào)劑 +4 | 李李不服輸 2026-03-26 | 4/200 |
|
|
|
[考研] 290分調(diào)劑求助 +3 | 吉祥止止陳 2026-03-25 | 3/150 |
|
|
|
[考研] 300分，材料，求調(diào)劑，英一數(shù)二 +5 | 超贊的 2026-03-24 | 5/250 |
|
|
|
[考研] 070300，一志愿北航320求調(diào)劑 +3 | Jerry0216 2026-03-22 | 5/250 |
|