The process of image search includes searching of images based on user given keywords. Most of the image retrieval techniques are based on text based image retrievals. But it has certain problems like images are time duplicated, low precision, and irrelevant. This paper represents the multiple scenario may occur due to sparse and noisy textual query. Because of this user cannot be always sure of perfect images being obtained in available time. To moderate image search user clicks are introduced into the search query so that the relevance between given query and result obtained should be maximized. User clicks are integrated to textual features to make refinement of textual query. The major bottleneck is likely mismatch between the image content and the given text. Image search re-ranking attempts to resolve this bottleneck by relying on both the text information and visual information during the image search process. This paper represents the trends in image search reranking and optimization with hyper graph.
Neha Sunil Jankar, Dr. D. S. Bhosle
Hyper Graph, VCLTR, Natural Language Processing, Data Mining, Information Retrieval, Discounted Cumulative Gain, Fast Alternating Linearization Method
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|Published in :
||Volume 2 | Issue 4 | July-August - 2016
|Date of Publication
Cite This Article
Neha Sunil Jankar, Dr. D. S. Bhosle, "Retrieval and Re-Ranking of Images with Better Optimization Using Hyper Graph", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 4, pp.76-79, July-August-2016.
URL : http://ijsrset.com/IJSRSET1623207.php