找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Data-Driven Personas; Bernard J. Jansen,Joni Salminen,Kathleen Guan Book 2021 Springer Nature Switzerland AG 2021

[復制鏈接]
樓主: 傳家寶
21#
發(fā)表于 2025-3-25 04:23:31 | 只看該作者
Creating Data-Driven Personaseneration (APG) system’s six stages. This is a data-driven persona development methodology employing non-negative matrix factorization to develop rich, holistic personas. We end the chapter by discussing other computer science domains’ contributions to this concept traditionally linked with HCI.
22#
發(fā)表于 2025-3-25 08:38:34 | 只看該作者
Selecting the Appropriate Persona Creation Methodta-driven personas from both researchers and practitioners, especially those who are new to personas, deploying personas in a new domain, or familiar with only one of the persona creation approaches. We end with some examples of the APG system that creates data-driven personas.
23#
發(fā)表于 2025-3-25 15:19:03 | 只看該作者
24#
發(fā)表于 2025-3-25 18:55:44 | 只看該作者
Saravanan Muthaiyah,Vivek Ajit Singhatic Persona Generation (APG), a data-driven-persona system, to illustrate the fundamental idea of motivating your organization to employ data-driven personas productively. Some of the insights in this chapter are useful for . persona project, although throughout the chapter we maintain a particular focus on data-driven personas.
25#
發(fā)表于 2025-3-25 22:58:33 | 只看該作者
Anjali Raghav,Sharad Vaish,Monika Guptaata-driven personas, including surveys, text quantification, and automated data collection. Finally, we discuss five central data challenges: (1) availability; (2) specifications; (3) unknown measurement error; (4) bias; and (5) ethical concerns. We conclude by presenting takeaways and educational questions.
26#
發(fā)表于 2025-3-26 01:36:16 | 只看該作者
27#
發(fā)表于 2025-3-26 04:38:41 | 只看該作者
28#
發(fā)表于 2025-3-26 10:42:51 | 只看該作者
29#
發(fā)表于 2025-3-26 16:16:29 | 只看該作者
1946-7680 ersonas enhance user understanding by combining the empathy inherent with personas with the rationality inherent in analytics using computational methods. Via the employment of these computational methods, the data-driven persona method permits the use of large-scale user data, which is a novel adva
30#
發(fā)表于 2025-3-26 18:13:32 | 只看該作者
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-26 09:51
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復 返回頂部 返回列表
徐闻县| 陇西县| 监利县| 方城县| 遂宁市| 屏东县| 凌云县| 昌乐县| 荆州市| 扎赉特旗| 昭平县| 五寨县| 囊谦县| 丹江口市| 无为县| 普兰店市| 吴堡县| 宝山区| 三穗县| 潞城市| 清远市| 武定县| 中方县| 贞丰县| 深州市| 安吉县| 永善县| 融水| 克什克腾旗| 宿松县| 双流县| 错那县| 罗甸县| 雷山县| 眉山市| 万山特区| 客服| 马鞍山市| 崇信县| 平陆县| 盘锦市|