An Image Retrieval Model Combining Ontology and Probabilistic Ranking

2013 ◽  
pp. 61-73
Author(s):  
Lisa Fan ◽  
Botang Li
Keyword(s):  
World Wide Web ◽  
Knowledge Representation ◽  
Cognitive Load ◽  
Image Retrieval ◽  
Web Application ◽  
World Wide ◽  
Experimental Results ◽  
Retrieval Method ◽  
Multimedia Documents ◽  
Model Combining

The demand for image retrieval and browsing online is growing dramatically. There are hundreds of millions of images available on the current World Wide Web. For multimedia documents, the typical keyword-based retrieval methods assume that the user has an exact goal in mind in searching a set of images whereas users normally do not know what they want, or the user faces a repository of images whose domain is less known and content is semantically complicated. In these cases it is difficult to decide what keywords to use for the query. In this chapter, we propose a user-centered image retrieval method based on the current Web, keyword-based annotation structure, and combining ontology guided knowledge representation and probabilistic ranking. A Web application for image retrieval using the proposed approach has been implemented. The model provides a recommendation subsystem to support and assist the user modifying the queries and reducing the user’s cognitive load with the searching space. Experimental results show that the image retrieval recall and precision rates are increased and therefore demonstrate the effectiveness of the model.

A User-Driven Ontology Guided Image Retrieval Model

2011 ◽  
pp. 272-282
Author(s):  
Lisa Fan ◽  
Botang Li
Keyword(s):  
World Wide Web ◽  
Knowledge Representation ◽  
Cognitive Load ◽  
Image Retrieval ◽  
Web Application ◽  
World Wide ◽  
Experimental Results ◽  
Retrieval Method ◽  
Multimedia Documents ◽  
Specific Goal

The demand for image retrieval and browsing online is growing dramatically. There are hundreds of millions of images available on the current World Wide Web. For multimedia documents, the typical keyword-based retrieval methods assume that the user has a specific goal in mind by using accurate query keywords in searching a set of images. Whereas the users may face with a repository of images whose domain is less known and content is semantically complicated, or the users may only generally know what they search for. In these cases it is difficult to decide what exact keywords to use for the query. In this article, we propose a user-centered image retrieval method that is based on the current Web, keyword-based annotation structure, and combining Ontology guided knowledge representation and probabilistic ranking. A prototype of web application for image retrieval using the proposed approach has been implemented. The model provides a recommendation subsystem to support and assist the user modifying the queries and reduces the user’s cognitive load with the searching space. Experimental results show that the image retrieval recall and precision rates increased and therefore demonstrates the effectiveness of the model.

ESIS ON THE WORLD WIDE WEB

1994 ◽  
Vol 05 (05) ◽  
pp. 805-809 ◽  
Author(s):  
SALIM G. ANSARI ◽  
PAOLO GIOMMI ◽  
ALBERTO MICOL
Keyword(s):  
World Wide Web ◽  
Web Application ◽  
World Wide ◽  
Markup Language ◽  
Command Line ◽  
Command Line Interface ◽  
The World ◽  
Hypertext Transfer Protocol ◽  
Hypertext Markup Language ◽  
Near Future

On 3rd November, 1993, ESIS announced its Homepage on the World Wide Web (WWW) to the user community. Ever since then, ESIS has steadily increased its Web support to the astronomical community to include a bibliographic service, the ESIS catalogue documentation and the ESIS Data Browser. More functionality will be added in the near future. All these services share a common ESIS structure that is used by other ESIS user paradigms such as the ESIS Graphical User Interface (Giommi and Ansari, 1993), and the ESIS Command Line Interface. A forms-based paradigm, each ESIS-Web application interfaces to the hypertext transfer protocol (http) translating queries from/to the hypertext markup language (html) format understood by the NCSA Mosaic interface. In this paper, we discuss the ESIS system and show how each ESIS service works on the World Wide Web client.

scholarly journals Visualization of typed links in Linked Data

2017 ◽  
Vol 70 (2) ◽  
pp. 179-199 ◽  
Author(s):  
Georg Neubauer
Keyword(s):  
World Wide Web ◽  
Semantic Web ◽  
Information Visualization ◽  
Web Application ◽  
Linked Data ◽  
World Wide ◽  
Processing Data ◽  
The World ◽  
Web Of Data ◽  
Practical Guidelines

The main subject of the work is the visualization of typed links in Linked Data. The academic subjects relevant to the paper in general are the Semantic Web, the Web of Data and information visualization. The Semantic Web, invented by Tim Berners-Lee in 2001, was announced as an extension to the World Wide Web (Web 2.0). The actual area of investigation concerns the connectivity of information on the World Wide Web. To be able to explore such interconnections, visualizations are critical requirements as well as a major part of processing data in themselves. In the context of the Semantic Web, representation of information interrelations can be achieved using graphs. The aim of the article is to primarily describe the arrangement of Linked Data visualization concepts by establishing their principles in a theoretical approach. Putting design restrictions into context leads to practical guidelines. By describing the creation of two alternative visualizations of a commonly used web application representing Linked Data as network visualization, their compatibility was tested. The application-oriented part treats the design phase, its results, and future requirements of the project that can be derived from this test.

Unifying Textual and Visual Cues for Content-Based Image Retrieval on the World Wide Web

1999 ◽  
Vol 75 (1-2) ◽  
pp. 86-98 ◽  
Author(s):  
Stan Sclaroff ◽  
Marco La Cascia ◽  
Saratendu Sethi ◽  
Leonid Taycher
Keyword(s):  
World Wide Web ◽  
Image Retrieval ◽  
Visual Cues ◽  
World Wide ◽  
Content Based Image Retrieval ◽  
The World

A CONTEXT-BASED APPROACH FOR COLOR IMAGE RETRIEVAL

2002 ◽  
Vol 16 (02) ◽  
pp. 239-255 ◽  
Author(s):  
JAU-LING SHIH ◽  
LING-HWEI CHEN
Keyword(s):  
Image Retrieval ◽  
Similarity Measure ◽  
Relevance Feedback ◽  
Color Image ◽  
Experimental Results ◽  
Retrieval Method ◽  
Feature Vectors ◽  
The Mean ◽  
Feedback Algorithm

In this paper, a color image retrieval method based on the primitives of images will be proposed. First, the context of each pixel in an image will be defined. Then, the contexts in the image are clustered into several classes based on the algorithm of fast noniterative clustering. The mean of the context in the same class is considered as a primitive of the image. The primitives are used as feature vectors. Since the numbers of primitives between images are different, a specially designed similarity measure is then proposed to do color image retrieval. To better adapt to the preferences of users, a relevance feedback algorithm is provided to automatically determine the weight of each primitive according to the user's response. To demonstrate the effectiveness of the proposed system, several test databases from Corel are used to compare the performances of the proposed system with other methods. The experimental results show that the proposed system is superior to others.

A COLOR IMAGE RETRIEVAL METHOD BASED ON COLOR MOMENT AND COLOR VARIANCE OF ADJACENT PIXELS

2002 ◽  
Vol 16 (01) ◽  
pp. 113-125 ◽  
Author(s):  
YUNG-KUAN CHAN ◽  
CHIN-CHEN CHANG
Keyword(s):  
Image Retrieval ◽  
Similarity Measure ◽  
Spatial Information ◽  
Color Image ◽  
Image Features ◽  
Experimental Results ◽  
Retrieval Method ◽  
Color Moment

This paper first introduces three simple and effective image features — the color moment (CM), the color variance of adjacent pixels (CVAP) and CM–CVAP. The CM feature delineates the color-spatial information of images, and the CVAP feature describes the color variance of pixels in an image. However, these two features can only characterize the content of images in different ways. This paper hence provides another feature CM–CVAP, which combines both, to raise the quality of similarity measure. The experimental results show that the image retrieval method based on the CM–CVAP feature gives quite an impressive performance.

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