Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  present our solutions for the WikipediaMM task at ImageCLEF 2008. The aim of this task is to investigate effective retrieval approaches in the context of a large-scale and heterogeneous collection of Wikipedia images that are searched by textual queries (and/or sample images and/or concepts) describing a user’s information need.  first experimented with a text-based image retrieval approach with query extension, where the expansion terms are automatically selected from a knowledge base that is (semi-)automatically constructed from Wikipedia.  show how this open, constantly evolving encyclopedia can yield inexpensive knowledge structures that are specifically tailored to effectively enhance the semantics of queries. Encouragingly, the experimental results rank in the first place among all submitted runs. The second approach  experimented with is content-based image retrieval (CBIR), in which  first train 1-vs-all classifiers for all query concepts by using the training images obtained by Yahoo! search, and then treat the retrieval task as visual concept detection in the given Wikipedia image set. By comparison, this approach performs better than other submitted CBIR runs. Finally,  experimented with a cross-media image retrieval approach by combining and re-ranking text-based and content-based retrieval results. Despite the final experimental results re not formally submitted before the deadline, this approach performs remarkably better than the text-based retrieval or CBIR approaches.
['Zhi Zhou', 'Yonghong Tian', 'Yuanning Li', 'Ting Liu', 'Tiejun Huang', 'Wen Gao']
I am writing a research paper on a idea PKU at ImageCLEF 2008: Experiments with Query Extension Techniques for Text-Based and Content-Based Image Retrieval.
[{"from": "human", "value": "I am writing a research paper on a idea PKU at ImageCLEF 2008: Experiments with Query Extension Techniques for Text-Based and Content-Based Image Retrieval."}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  present our solutions for the WikipediaMM task at ImageCLEF 2008. The aim of this task is to investigate effective retrieval approaches in the context of a large-scale and heterogeneous collection of Wikipedia images that are searched by textual queries (and/or sample images and/or concepts) describing a user\u2019s information need.  first experimented with a text-based image retrieval approach with query extension, where the expansion terms are automatically selected from a knowledge base that is (semi-)automatically constructed from Wikipedia.  show how this open, constantly evolving encyclopedia can yield inexpensive knowledge structures that are specifically tailored to effectively enhance the semantics of queries. Encouragingly, the experimental results rank in the first place among all submitted runs. The second approach  experimented with is content-based image retrieval (CBIR), in which  first train 1-vs-all classifiers for all query concepts by using the training images obtained by Yahoo! search, and then treat the retrieval task as visual concept detection in the given Wikipedia image set. By comparison, this approach performs better than other submitted CBIR runs. Finally,  experimented with a cross-media image retrieval approach by combining and re-ranking text-based and content-based retrieval results. Despite the final experimental results re not formally submitted before the deadline, this approach performs remarkably better than the text-based retrieval or CBIR approaches."}]