Google images search engine - Bookshelf
The experimental results show that the performance of the CSISE engine (based on the proposed method) is comparable to the popular online image search engines as well as accurate with a higher rate (average precision of 71%) than existing ...
About this book
Due to rapid exponential growth in data, a couple of challenges we face today are how to handle big data and analyze large data sets. An IBM study showed the amount of data created in the last two years alone is 90% of the data in the world today. We have especially seen the exponential growth of images on the Web, e.g., more than 6 billion in Flickr, 1.5 billion in Google image engine, and more than 1 billion images in Instagram . Since big data are not only a matter of a size, but are also heterogeneous types and sources of data, image searching with big data may not be scalable in practical settings. We envision Cloud computing as a new way to transform the big data challenge into a great opportunity. In this thesis, we intend to perform an efficient and accurate classification of a large collection of images using Cloud computing, which in turn supports semantic image searching. A novel approach with enhanced accuracy has been proposed to utilize semantic technology to classify images by analyzing both metadata and image data types. A two-level classification model was designed (i) semantic classification was performed on a metadata of images using TF-IDF, and (ii) image classification was performed using a hybrid image processing model combined with Euclidean distance and SURF FLANN measurements. A Cloud-based Semantic Image Search Engine (CSISE) is also developed to search an image using the proposed semantic model with the dynamic image repository by connecting online image search engines that include Google Image Search, Flickr, and Picasa. A series of experiments have been performed in a large-scale Hadoop environment using IBM's cloud on over half a million logo images of 76 types. The experimental results show that the performance of the CSISE engine (based on the proposed method) is comparable to the popular online image search engines as well as accurate with a higher rate (average precision of 71%) than existing approaches.
Data Search Engines, Search Engine, Wolfram Alpha, Jumper 2. 0, Retrievalware, Human Flesh Search Engine, Bacengine, Trex Search Engine
Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online.
About this book
Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Pages: 202. Chapters: Code search engines, Human edited search engines, Image search, Internet search engines, Ranking functions, Search engine software, Google Search, Archie search engine, Web crawler, Wide area information server, Lycos, CiteSeer, Inktomi, Bing, Yahoo!, List of academic databases and search engines, Baidu, Internet search engines and libraries, Web search engine, Learning to rank, Mobile search, Personalization, List of search engines, Google search features, Content-based image retrieval, ChaCha, Cuil, Excite, Wikia Search, Wolfram Alpha, Yandex, Alexa Internet, Mahalo.com, Ask.com, TigerLogic, Picsearch, TheFind.com, Viewzi, Open Text Corporation, Google Image Labeler, Yahoo! Search, Travel website, SeeqPod, EB-eye, Judy's Book, Jumper 2.0, AltaVista, Truveo, Science.gov, Human flesh search engine, SearchMe, Carrot2, Forestle, Taptu, Color Layout Descriptor, Powerset, Wazap!, RetrievalWare, Search engine technology, Tf-idf, Business.com, Singingfish, Knowledge tags, Duck Duck Go, Fabasoft Mindbreeze, LeapFish, Quaero, Become.com, Picollator, Clusty, Nestoria, OpenSearch, GenieKnows, Local search, Seznam.cz, Greenpilot, Yamli, Globrix, List of CBIR engines, Search-based application, Selection-based search, TipTop Technologies, Okapi BM25, Nutch, Semantic search, Scour, Search engine submission, Bioinformatic Harvester, Quepasa, Blekko, Yebol, Ohloh, Video search engine, InfoSpace, TinEye, A9.com, YaCy, Ixquick, Distributed search engine, Blingo, Copernic, Songza, Naver, Pixsta, Grantsmart, NOZA, Inc., SeatGeek, DataparkSearch, Maktoob, DeeperWeb, Convera Corporation, Polycola, Seekda, Best of the Web Directory, Exalead, Twing, Google Code Search, OpenGrok, GetApp.com, ScientificCommons, Ziplocal, Aliweb, Wikio, Content Discovery Platform, Google Images, GoodSearch, HighBeam Research, BACEngine, Munax, Nextbio, Pubge...
For example, some of the most useful specialty search engines allow web users to search blogs, images, auction sites, social bookmarks, or classified ads. Although you can use Google to search for practically any kind of information, using ...
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