Finding top similar images from a database using SIFT

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I am working on project and using SIFT features (OpenCV implementation) for image matching. I need to return top 10-15 images in the database which are similar to the query image. I'm using a visual bag-of-words approach to make a vocabulary first and then do the matching. I've found similar questions but didn't find the appropriate answer.

Here is code to generate a dictionary from database images:

char * filename = new char[100];        

Mat input;

//To store the keypoints that will be extracted by SIFT
vector<KeyPoint> keypoints;

//To store the SIFT descriptor of current image
Mat descriptor;

//To store all the descriptors that are extracted from all the images.
Mat featuresUnclustered;

//The SIFT feature extractor and descriptor
SiftDescriptorExtractor detector;

for(int f=1;f<20;f++)            // 20 images in database
{       
    sprintf(filename,"/home/kamikaze/testing/bagofwords/images/%i.jpg",f);

    input = imread(filename, CV_LOAD_IMAGE_GRAYSCALE); //Load as grayscale              

    //detect feature points
    detector.detect(input, keypoints);

    //compute the descriptors for each keypoint
    detector.compute(input, keypoints,descriptor);      

    //put the all feature descriptors in a single Mat object 
    featuresUnclustered.push_back(descriptor);      

}

int dictionarySize=200;

TermCriteria tc(CV_TERMCRIT_ITER,100,0.001);

int retries=1;

int flags=KMEANS_PP_CENTERS;

//Create the BoW (or BoF) trainer
BOWKMeansTrainer bowTrainer(dictionarySize,tc,retries,flags);

//cluster the feature vectors
Mat dictionary=bowTrainer.cluster(featuresUnclustered); 

//store the vocabulary
FileStorage fs("dictionary.yml", FileStorage::WRITE);
fs << "vocabulary" << dictionary;
fs.release();   

Here's my code to extract a BoW descriptor from query image using this vocabulary:

Mat dictionary; 
FileStorage fs("dictionary.yml", FileStorage::READ);
fs["vocabulary"] >> dictionary;
fs.release();   

Ptr<DescriptorMatcher> matcher(new FlannBasedMatcher);
Ptr<FeatureDetector> detector(new SiftFeatureDetector());
Ptr<DescriptorExtractor> extractor(new SiftDescriptorExtractor);    
BOWImgDescriptorExtractor bowDE(extractor,matcher);
bowDE.setVocabulary(dictionary);

char * filename = new char[100];
char * imageTag = new char[10];

//open the file to write the resultant descriptor
FileStorage fs1("descriptor.yml", FileStorage::WRITE);  

//the image file with the location. 
sprintf(filename,"G:\\testimages\\image\\1.jpg");       
Mat img=imread(filename,CV_LOAD_IMAGE_GRAYSCALE);       

//To store the keypoints that will be extracted by SIFT
vector<KeyPoint> keypoints;     

//Detect SIFT keypoints (or feature points)
detector->detect(img,keypoints);

//To store the BoW (or BoF) representation of the image
Mat bowDescriptor;      

//extract BoW (or BoF) descriptor from given image
bowDE.compute(img,keypoints,bowDescriptor);

sprintf(imageTag,"img1");           
fs1 << imageTag << bowDescriptor;       

fs1.release();

I don't know how can I make use of bowDescriptor for getting similar images in the database.