Classification And Prediction Analysis Of Multimedia Data

Introduction: Classification and predictive modeling have been used for mining multimedia data, especially in scientific research, such as astronomy, seismology, and geo scientific research. Moreover, in-depth statistical pattern analysis methods are popular for distinguishing subtle features and building high-quality models.

Example: Classification and prediction analysis of astronomy data. Taking sky images that have been carefully classified by astronomers as the training set, we can construct models for the recognition of galaxies, stars, and other stellar objects, based on properties like magnitudes, areas, intensity, image moments, and orientation. A large number of sky images taken by telescopes or space probes can then be tested against the constructed models in order to identify new celestial bodies. Similar studies have successfully been performed to identify volcanoes on Venus.

Data preprocessing is important when mining image data and can include data cleaning, data transformation, and feature extraction. Aside from standard methods used in pattern recognition, such as edge detection and Hough transformations, techniques can be explored, such as the decomposition of images to eigenvectors or the adoption of probabilistic models to deal with uncertainty. Since the image data are often in huge volumes and may require substantial processing power, parallel and distributed processing are useful. Image data mining classification and clustering are closely linked to image analysis and scientific data mining, and thus many image analysis techniques and scientific data analysis methods can be applied to image data mining.

The popular use of the WorldWideWeb has made the Web a rich and gigantic repository of multimedia data. The Web not only collects a tremendous number of photos, pictures, albums, and video images in the form of on-line multimedia libraries, but also has numerous photos, pictures, animations, and other multimedia forms on almost every Web page. Such pictures and photos, surrounded by text descriptions, located at the different blocks of Web pages, or embedded inside news or text articles, may serve rather different purposes, such as forming an inseparable component of the content, serving as an advertisement, or suggesting an alternative topic. Furthermore, these Web pages are linked with other Web pages in a complicated way. Such text, image location, and Web linkage information, if used properly, may help understand the contents of the text or assist classification and clustering of images on the Web. Data mining by making good use of relative locations and linkages among images, text, blocks within a page, and page links on the Web becomes an important direction in Web data analysis.