| DC 欄位 |
值 |
語言 |
| DC.contributor | 軟體工程研究所 | zh_TW |
| DC.creator | 凌杰甫 | zh_TW |
| DC.creator | Lin Jei Fu | en_US |
| dc.date.accessioned | 2016-8-25T07:39:07Z | |
| dc.date.available | 2016-8-25T07:39:07Z | |
| dc.date.issued | 2016 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=103525012 | |
| dc.contributor.department | 軟體工程研究所 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 近年來，地理位置服務(location-based services) 的使用人口伴隨著行動化裝置的普及而快速成長。使用者只要輕鬆地輸入關鍵字，即可透過行動裝置隨時隨地獲取周遭的資訊，進而快速地安排行程。但隨著各家的服務如雨後春筍般地不斷推出，要如何能吸引使用者的目光成了一個重要的課題。
我們希望透過不斷更新資料庫，以提供最新與最正確的訊息來吸引使用者，而其中最能抓住大眾目光的資訊便是圖片，相較單純以文字敘述店家，透過商品或是店家實際圖片的呈現更能引起使用者的興趣。
由於大部分POI來源的黃頁以文字訊息居多，因此圖片的資訊大多需要以人工的方式去新增。為了減少時間與人力消耗，透過所建立的系統，可為POI資料庫中沒有圖片的商家，從網路上的資源尋找可以配對的圖片與相關資料。
隨著社群網站和個人網站的興起，我們可以從網路上獲得大量的圖片。因為這些鑲嵌於網頁中的圖片內隱含了很多可利用的訊息，故我們在收集圖片將這些資料一併收集，同時也利用網路爬蟲收集店家資訊，並從中萃取店家的相關特徵資訊。最後從圖片中挑選相關資訊最符合特徵者作為店家配對的圖片。 | zh_TW |
| dc.description.abstract | In recent years, consumer-focused location-based services have been growing exponentially. People can get the nearby information or plan a trip easily by using these applications. However, there is tough competition between these similar applications. Hence how to attract users become a big challenge.
People usually choose the service which provides the latest and the most correct information. In order to achieve this goal, we need to constantly update the database. In this paper, our goal is to build a system which can renew POI data automatically. We want to update the information of POIs such as telephones, business hours and images. Among all of these data, images are consider as the most important type since they can attract users’ eyes.
In this study, we have designed an approach to find the correct images for POIs in several steps. First, we use a search engine to collect a POI’s information and extract its features. The Second part is to collect the images from the web pages. With the popularity of the internet, there are lots of resources like social media or blogs. For each image, we collect the related information such as title or Alt and the near-by texts. Finally, we match the POI’s feature with image’s information to find the best image. | en_US |
| DC.subject | 爬蟲 | zh_TW |
| DC.subject | 圖片與POI配對 | zh_TW |
| DC.subject | crawler | en_US |
| DC.subject | POI and image pairing | en_US |
| DC.subject | Image Retrieval | en_US |
| DC.title | 商家與圖片配對研究 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.title | Finding representative images for POIs | en_US |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |