Click-Search: 基於互動式圖片關鍵詞轉換的資訊搜尋使用者介面

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研究生：	楊平京 Yang, Ping Jing
論文名稱：	Click-Search: 基於互動式圖片關鍵詞轉換的資訊搜尋使用者介面 Click-Search: Supporting Information Search with Interactive Image-to-Keyword Query Formulation
指導教授：	王浩全 Wang, Hao Chuan
口試委員:	李峻德 Lee, Jiun De 林怡伶 Lin, Yi Ling
學位類別：	碩士 Master
系所名稱：	電機資訊學院 - 資訊工程學系 Computer Science
論文出版年：	2016
畢業學年度：	104
語文別：	英文
論文頁數：	41
中文關鍵詞：	搜索引擎介面、基於互動的搜索、信息氣味、重建查詢詞
外文關鍵詞：	search user interface, searching through interaction, information scent, query formulation
相關次數：	點閱：3 下載：0
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在人們每天的生活中，進行搜索或者使用搜索引擎工具已經成為了獲取資訊的必要手段。通過Google，Bing以及Yahoo搜索等商用產品，人們可以快速定位到自己常去的網站與服務，了解最新聞事件與探索新知。不僅如此，在社群網站Facebook，圖片為主的線上社群Instgram，以及閱讀寫作分享平台Medium等以使用者產生內容(User Generated Content, UGC）為基礎的服務之中，資訊搜尋也已是不可或缺的一個功能。然而，如何有效地輔助使用者完成搜索，滿足使用者的需求依然是一待解難題。
如何幫助使用者在他們尚不知道如何用語言去表達搜索目標時的情況下去進行搜尋依然是一個非常具有挑戰性的設計難題。進一步來說，即使使用者知道如何表達，他們花費在思考以及建構搜尋關鍵詞的過程的認知成本也是相當可觀。在這篇論文中，我們提出了Click-Search。利用Click-Search，用戶可以通過選擇和截取畫面的部分內容表達搜索目的。系統將會自動轉換被選取的圖片區塊成為關鍵詞。這一轉換工作背後是由群眾外包所構建完成的資料庫作為基礎。透過一系列的用戶研究，我們發現Click-Search能夠有效支持不同類型的資訊搜尋行為。我們討論透過與圖片互動以進行搜索這一創新互動方法的設計啟示。

Information search is a common yet important task in everyday work and life. It remains a challenging design issue how to help users search for information or things they don’t necessarily know how to express with words. Also, even when people know how to express, the cognitive cost required to retrieve the concepts and formulate the queries can be excessive. In this paper, we present Click-Search, a search user interface that allows people to indicate their search intents by merely selecting and cropping segments of image contents. The system automatically converts selected image segments to keywords based on known associations between image pixels and semantic labels created by prior crowdsourced image tagging. Through a user study, we found that Click-Search can support a range of searching activities effectively. We discuss the implications of the new approach of searching through interactions with images.

Abstract    i
Table of Contents    iii
Acknowledgement    v
List of Figures    vi
List of Tables    vii
Chapter 1    Introduction    1
Chapter 2    Background: Mental Model of Cognitive Search    5
1.    Mental Processes of Information Search    5
2.    Query Formulation and Reformulation    6
3.    Information Foraging as Iterative Search    7
Chapter 3    Background: Images Searching and Labelling    9
1.    Text-based Image Retrieval and Image Tagging    9
2.    Content-based Image Retrieval    11
3.    Interaction-based Information Search    11
Chapter 4    Click-Search System    13
1.    User Interaction Model – Converting needs to query    13
1.1.    Hovering over the images    13
1.2.    Click and cycle segments from the image    13
1.3.    Crop segments and save for later iteration    14
2.    User Interaction Model – Refining queries to target    15
2.1.    Save image segments to work space    15
2.2.    Update Tag Clouds in Scent Space    16
3.    Prototyping    17
2.1.    Back-end Database    17
2.2.    Image Retrieval    18
2.3.    System Summary    19
4.    Evaluation Preparation    20
3.1.    Baseline - Regular Search Interface    20
3.2.    Participants of the evaluation    21
Chapter 5    Part 1: Finding objects search    23
1.    Introduction    23
2.    Experimental Design    23
3.    Procedure    24
4.    Measures    24
5.    Results    25
5.1.    Time to find objects    26
5.2.    Amount of text queries submitted    26
5.3.    Amount of hovering over images    27
Chapter 6    Part 2: Search-based brainstorming    28
1.    Introduction    28
2.    Experimental Design    28
3.    Procedure    29
4.    Measures    29
5.    Results    30
Chapter 7    System Efficiency and Satisfaction    31
1.    Participants    31
2.    Questionnaire Description    31
3.    Evaluation Results    32
Chapter 7    Discussion    34
1.    Verbalize the Unverbalized, Search the Unsearchable    34
2.    Using Images as an External Search Memory    34
3.    Interactions with Images as Relevance Feedback    35
4.    Diversifying Information Search    36
5.    Limitation and Future Work    37
Chapter 9    Conclusion    38
References    39

                                

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