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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/9467

    Title: 以人為目標使用社會化語義認證共同實踐體之搜尋;Identification of communities of practice for people search with social semantics
    Authors: 林起民;Chi-min Lin
    Contributors: 資訊工程研究所
    Keywords: 社會網路;社會化語意;正規化概念分析;實踐共同體;Community of practice;Social network;Social semantic;Formal concept analysis
    Date: 2007-06-25
    Issue Date: 2009-09-22 11:48:26 (UTC+8)
    Publisher: 國立中央大學圖書館
    Abstract: 隨著網際網路的蓬勃發展,資訊的取得、傳播、儲存變的更加的便利,也正因為如此,網際網路成為人們獲取知識的重要媒介。像是在早期的人們會透過電子佈告欄、論壇一類的網路服務進行問題討論,來互動及學習,他們經由文字、圖片的方式描述完自己的問題或自己的看法後,等待其他的成員一起參與交流。而由於這種討論的方式沒辦法很即時地反應使用者的需求,使用者必須被動地等待其他人的回應;同時網際網路中可供個人分享資訊的媒體增加,各大入口網站都提供了網頁的空間可以讓一般人架設自己的網頁,導致了網路中的資料量大增,資料分享的動機與傳遞已經不是被人們所關注的焦點,重要是如何找到正確而有幫助的資料。所以人們為了簡化這個知識擷取的過程,開發出了搜尋引擎的機制,它可以藉由使用者所產生的關鍵字,來找出相對應的資源列表。 但是存放在網路上的這些資訊仍無法正確而有效率的被利用,真正有用的資訊和我們搜尋到的結果相比,準確率不到百分之一。其中最主要的原因是由於人類與機器在認知上有著相當大的差異,用於存放這些資訊的機器只能以字元的方式在網路上進行定位、比對,可是人類對於事物卻是以概念的方式去進行記憶、關聯的。針對這個方面,有許多的專家致力於解析人們的語義或是透過權重排序的方式,希望藉此來彌補兩者間的差異,不過目前仍無法完善地進行解決。因此,現在還出現另一種新的求解型態,就是社會化語意,這種方式藉由社會化網路中的具有該知識的人撰寫描述來幫使用者過濾雜訊,讓幫助使用者更快的找到想要的資訊。可惜的一點是,他們的作法雖然有助於語意的表達,但還是缺乏一些像是Web 2.0所強調的互動性。 所以我們認為開發一套找人的系統是必要的,因為人跟電腦間在認知的本質上就有差異,人是以概念為單位來進行記憶、關聯、推論,至於電腦則是以字元的方式儲存,然後藉由預先制定的法則來進行關聯、推論。不過就目前的技術而言,人們並沒有辦法完善的彌補這兩者之間的差異,所以我們想要處理的情況就是遇到問題又無法透過網路來求得解答時,我們的系統該如何去協助使用者。而在這邊我們想到的解決方式是轉移搜尋的目標,當我們搜尋的對象是人而非一大群資料的時候,由於查詢者和被查詢者具有相同的思考模式,故可以使用比較抽象大範圍的關鍵字去查,藉由提高該關鍵字的抽象層次來解決要自己產生主要關鍵字的問題,並且在用抽象層次所找到適合的人選後,再透過與對方的互動來完成概念的傳遞。經由這樣的方式我們可以把語義問題轉嫁到被搜尋的人身上,同時也不必去擔心搜尋到的資訊過於繁雜等問題。故可以減少使用者產生許多關鍵字的負擔,並依然可以取得精確的結果。這種有別於過去針對資料的搜尋方式而轉變成對於人對於社群的搜尋需求,被稱為社群導向式搜尋。所以我們的研究就是希望能利用基於FOAF所描述的社會化網路來架構一個尋人的平台,並把社會化網路中的人所提出的概念用正規化概念分析來正規化,同時將他們依據概念相似度分組形成實踐共同體,提供使用者來找到可以幫忙自己的人。最後透過我們的系統來實現社會化語意的一些理想,以解決上述的一些問題。 According to the development of internet recently, the acquirement, transmission, and storage of information become more convenient. Thus the internet is a necessary media to people for their knowledge deriving. People will discuss through some web service such as BBS or forum to communicate with each other. They use context to describe their problems or to perform their opinions and after that they wait for others’ collaboration. But because of lacking immediately response to users and the way of sharing personal knowledge on internet increasing, a new technology so called search engine was raised. It can help user to find out their wanted resources from a mass of information through the keyword matching. Still the information on internet couldn’t be efficiently used. The main reason is that there is a cognitive gap between human and machine. Machines use the characters to express and to cognize all kinds of data on the internet, while human beings take things and the relevant connections as concepts to infer or to memorize. In order to solve these questions, there are many researchers devote to analysis queries generate from users of the search engine. They would like to find out the semantic exist in user’s requests at different kinds of situations. But they didn’t find a general solution to make up that gap. Thus a new solution model was proposed which could help people to filter out the irrelevant stuff named social semantic. Through communal annotation of the resources which will help machine to draw inference, user could get more precise results. Summarize the reason mentioned above we found that it is necessary to develop a system for searching people. Because when the search target is changed to human beings, we can take the found one as a collaborative filter which may help us filter out the nonsense about the topic. Through abstracting concepts of the search target people will able to find a knowledgeable one to answer their question. So our research is to establish a social network based platform for people search. And we take the advantage of the formal concept analysis to identify the community of practice which gathering the group of people with similar concepts. With that kind of identification our system provide a possibility to find someone who knows what you say and solve your problem rapidly.
    Appears in Collections:[資訊工程研究所] 博碩士論文

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