In this paper, we introduce a new subclasses of univalent functions defined in the open unit disc involving DziokSrivastava Operator . The results on modified Hadamard product ,Holder inequalities and closure properties under integral transforms are discussed.
Traditional information retrieval systems lack consistent semantic description of information i.e. they fail to meet users' need due to lack of applying semantic identification to extract the information from the available information. Use of semantic equivalent of the user query will improve the efficiency of the search. In this paper, we propose a framework for semantic based information retrieval. Here we find the concepts that user specify in their query by analyzing the semantic equivalencies. The result which is a set of alternate queries to the main search query is then compared with the existing keyword based system's result. Then, according to the alternate queries' search results, the main queries result gets rearranged by assigning new weights. We further personalize the search and then re-rank the results on user preference. The proposed semantic retrieval model is combined with keyword based model to achieve completeness of the knowledge base. The model which we propose is helping to project the most relevant result URLs to the higher ranks.
The process of demonstrating, organizing and evaluating the pictures regarding the information despite of evaluating pictures is the field of Content Based Image Retrieval (CBIR). Here we work on the salvage of images based not on keywords or explanations but on features haul out directly from the image data. The well-organized algorithms of salvage algorithms are already proposed. Content Based Image Retrieval has replaced Text Based Image Retrieval. CBIR is processed by more methods and research scientists are working to improve the accuracy of the technique. The project presents that the ROI from an image is retrieved and it retains the image based on Teacher Learning Based Optimization genetic algorithm. The retrieval of the image improves the efficiency based on two metrics such as precision and recall which is the main advantage of the project. The issue of Content Based Image Retrieval systems to provide the semantic gap and to determine the variation between the structure of visual objects and definition of semantics. From the human visual system the visual courtesy is more projected for the purpose of Content Based Image Retrieval. The new similarity based matching method is described based on the saliency map which retains the courtesy values and the regions of interest are hauled out.
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