維基百科:標註/關於
維基評級標記是一套軟體的名字,也是一項主題(WikiProject)的名字。在這個主題中,我們產生出包含被「標記」的維基編輯的資料集,而這套軟體簡化了這項工作。
目標和範圍
本計劃致力於維基社群所急,製作標記資料庫。此資料庫用途多樣,例如研究分析(如對新來者特性做定性分析[1]、編輯的互動作用[2])與開發進階維基工具(如en:User:ClueBot NG和en:WP:STiki使用的模型)。一般製作此類資料庫並不易,它需要一小群人需要投入大量時間精力,手工解碼出大小適當的資料庫。
我們關注:(1)生成重要標籤資料庫時機的認定;(2)儘可能廣泛的分配工作;(3)讓手工編碼巨量資料庫的工作簡單高效。請見我們最近的活動列表。您若希望參與,請在成員名單簽名。您有製作標籤資料庫的想法,請於討論頁留言。
我如何幫忙?
您可透過以下幾種方式參與此專案。
合作專案
修訂版本評分作為服務
Many of Wikipedia's most powerful tools rely on machine classification of edit quality. In this project, we'll construct a public queryable API of machine classified scores for revisions. It's our belief that by providing such a service, we would make it much easier to build new powerful wiki tools and extend current tools to new wikis. In order to build powerful machine classifiers, we must start with high quality labeled data. That's where Wiki labels comes in. See WP:Labels/Edit quality.
The primary way that wiki tool developers will take advantage of this project is via a restful web service and scoring system we call ORES (Objective revision evaluation service). ORES provides a web service that will generate scores for revisions on request. For example, http://ores.wmflabs.org/scores/enwiki?revids=34854258&models=reverted asks for the score of the "reverted" model for revision #34854258 in English Wikipedia.
參考資料
- ^ Halfaker, A., Geiger, R. S., Morgan, J. T., & Riedl, J. (2012). The rise and decline of an open collaboration system: How Wikipedia’s reaction to popularity is causing its decline. American Behavioral Scientist, 0002764212469365. summary full paper
- ^ m:Grants:IEG/Editor Interaction Data Extraction and Visualization