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Query Difficulty Estimation for Image Search

With Query Reconstruction Error

ABSTRACT

Current image search engines suffer from a radical variance in retrieval performance over different queries. It is therefore desirable to identify those “difficult” queries in order to handle them properly. Query difficulty estimation is an attempt to predict the performance of the search results returned by an image search system. Most existing methods for query difficulty estimation focus on investigating statistical characteristics of the returned images only, while neglecting very important information, i.e., the query and its relationship with returned images. This relationship plays a crucial role in query difficulty estimation and should be explored further. In this paper we propose a novel query difficulty estimation method with query reconstruction error. This method is proposed based on the observation that, given the images returned for an unknown query, we can easily deduce what the query is from those images if the search results are high quality.

EXISTING SYSTEM	PROPOSED SYSTEM
EXISTING CONCEPT:- In existing methods the query difficulty estimation focus on investigating statistical characteristics of the returned images only, while neglecting very important information. The query and its relationship will have returned images. This relationship plays a crucial role in query difficulty estimation and should be explored further.	PROPOSED CONCEPT:- The proposed system is based on the observation that, given the images returned for an unknown query, we can easily deduce what the query is from those images if the search results are high quality. We propose to predict the query difficulty by measuring to what extent the original query can be recovered from the image search results.
EXISTING ALGORITHM:- Query difficulty estimation.	PROPOSED ALGORITHM:- Query Reconstruction Error-Based Query Difficulty Estimation.
ALGORITHM DEFINITION:- The image retrieval performance by analyzing the Clarity Score between the query image and the returned images This method leverages the noisy textual information and neglects the rich contents of the returned images.	ALGORITHM DEFINITION:- The proposed query difficulty estimation with query reconstruction error investigates the consistency between the original textual query and the reconstructed visual query to predict the query performance. The visual query is reconstructed from the image search results and it represents the visual theme of the returned images.
DRAWBACKS:- The query can’t be returned to retrieve the images. Same images only retrieved.	ADVANTAGES:- It uses the initial text-based search result for pre-filtering. The efficiency of the retrieval process can be largely improved.