東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Focused image search in the social Web.

University of Louisville.

FindBook

Google Book

Amazon

博客來

Focused image search in the social Web.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Focused image search in the social Web./
作者:	Zhang, Zhiyong.
面頁冊數:	129 p.
附註:	Adviser: Olfa Nasraoui.
Contained By:	Dissertation Abstracts International70-03B.
標題:	Computer Science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3352064
ISBN:	9781109087895

Focused image search in the social Web.
Zhang, Zhiyong.

Focused image search in the social Web. - 129 p.

Adviser: Olfa Nasraoui.

Thesis (Ph.D.)--University of Louisville, 2008.

Recently, social multimedia-sharing websites, which allow users to upload, annotate, and share online photo or video collections, have become increasingly popular. The user tags or annotations constitute the new multimedia "meta-data". We present an image search system that exploits both image textual and visual information. First, we use focused crawling and DOM Tree based web data extraction methods to extract image textual features from social networking image collections. Second, we propose the concept of visual words to handle the image's visual content for fast indexing and searching. We also develop several user friendly search options to allow users to query the index using words and image feature descriptions (visual words). The developed image search system tries to bridge the gap between the scalable industrial image search engines, which are based on keyword search, and the slower content based image retrieval systems developed mostly in the academic field and designed to search based on image content only. We have implemented a working prototype by crawling and indexing over 16,056 images from flickr.com, one of the most popular image sharing websites. Our experimental results on a working prototype confirm the efficiency and effectiveness of the methods, that we proposed.

ISBN: 9781109087895Subjects--Topical Terms:

626642
Computer Science.

Focused image search in the social Web.
LDR:02148nam 2200277 a 45 001 852588
005 20100630
008 100630s2008 ||||||||||||||||| ||eng d
020 $a 9781109087895
035 $a (UMI)AAI3352064
035 $a AAI3352064
040 $a UMI $c UMI
100 1 $a Zhang, Zhiyong. $3 1018533
245 1 0 $a Focused image search in the social Web.
300 $a 129 p.
500 $a Adviser: Olfa Nasraoui.
500 $a Source: Dissertation Abstracts International, Volume: 70-03, Section: B, page: 1773.
502 $a Thesis (Ph.D.)--University of Louisville, 2008.
520 $a Recently, social multimedia-sharing websites, which allow users to upload, annotate, and share online photo or video collections, have become increasingly popular. The user tags or annotations constitute the new multimedia "meta-data". We present an image search system that exploits both image textual and visual information. First, we use focused crawling and DOM Tree based web data extraction methods to extract image textual features from social networking image collections. Second, we propose the concept of visual words to handle the image's visual content for fast indexing and searching. We also develop several user friendly search options to allow users to query the index using words and image feature descriptions (visual words). The developed image search system tries to bridge the gap between the scalable industrial image search engines, which are based on keyword search, and the slower content based image retrieval systems developed mostly in the academic field and designed to search based on image content only. We have implemented a working prototype by crawling and indexing over 16,056 images from flickr.com, one of the most popular image sharing websites. Our experimental results on a working prototype confirm the efficiency and effectiveness of the methods, that we proposed.
590 $a School code: 0110.
650 4 $a Computer Science. $3 626642
650 4 $a Information Science. $3 1017528
690 $a 0723
690 $a 0984
710 2 $a University of Louisville. $3 1017614
773 0 $t Dissertation Abstracts International $g 70-03B.
790 $a 0110
790 1 0 $a Nasraoui, Olfa, $e advisor
791 $a Ph.D.
792 $a 2008
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3352064