Relevance feedback for shape query refinement
نویسندگان
چکیده
In this paper we propose to incorporate a feedback loop, into the ordinal correlation framework and apply it to shapebased image retrieval. The user’s feedback on the relevance of the retrieval results is used to tune the weights of the similarity measure. Statistics from the features of both relevant and irrelevant items are used to estimate the weights. Moreover, the information accumulated from previous retrieval iterations is used in the weights estimation. A simple measure of the discrimination power is proposed and used to show that the relevance feedback increases the capability of the ordinal correlation scheme to discriminate between relevant and irrelevant objects.
منابع مشابه
Query expansion based on relevance feedback and latent semantic analysis
Web search engines are one of the most popular tools on the Internet which are widely-used by expert and novice users. Constructing an adequate query which represents the best specification of users’ information need to the search engine is an important concern of web users. Query expansion is a way to reduce this concern and increase user satisfaction. In this paper, a new method of query expa...
متن کاملDocument Image Retrieval Based on Keyword Spotting Using Relevance Feedback
Keyword Spotting is a well-known method in document image retrieval. In this method, Search in document images is based on query word image. In this Paper, an approach for document image retrieval based on keyword spotting has been proposed. In proposed method, a framework using relevance feedback is presented. Relevance feedback, an interactive and efficient method is used in this paper to imp...
متن کاملMultiple Strategies for Relevance Feedback in Image Retrieval
Retrieval by similarity in image databases can be accomplished by comparing features extracted from a sample image to the features extracted from the images in the database. Relevance feedback is a technique of query refinement used in text as well as in image retrieval systems which is based on user selection of the most relevant images among the ones retrieved, whose features are used to modi...
متن کاملTwo Stages Refinement of Query Translation for Pivot Language Approach to Cross Lingual Information Retrieval: A Trial at CLEF 2003
This paper reports experimental results of cross-lingual information retrieval from German to Italian. The authors are concerned with CLIR in the case that available language resources are very limited. Thus transitive translation of queries using English as a pivot language was used to search Italian document collections for German queries without any direct bilingual dictionary or MT system o...
متن کاملRanking Refinement via Relevance Feedback in Geographic Information Retrieval
Recent evaluation results from Geographic Information Retrieval (GIR) indicate that current information retrieval methods are effective to retrieve relevant documents for geographic queries, but they have severe difficulties to generate a pertinent ranking of them. Motivated by these results in this paper we present a novel re-ranking method, which employs information obtained through a relevan...
متن کامل