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We have become able to get enough approvable images of a target object just by submitting its object-name to a conventional keyword-based Web image search engine. However, because the search results rarely include its uncommon images, we can often get only its common images and cannot easily get exhaustive knowledge
Most researches on Image Retrieval (IR) have aimed at clearing away noisy images and allowing users to search only acceptable images for a target object specified by its object-name. We have become able to get enough acceptable images of a target object just by submitting its object-name to a conventional keyword
engineering problems. To reuse previous design resolution, this paper presents a function based patent retrieval approach in which the initial keywords are represented as “verb + noun”, and then the verbs and nouns are automatically expanded into verb set and noun set using Functional Basis and WordNet. The verb
expansion. Wu-Palmer similarity model is applied in retrieving the output from the database. The output shows that expanded query produces better results in terms of qualitative & quantitative rather than unexpanded query. Query expansion increases the number of keywords which help in fetching similar patents. The results of
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.