Integrating neurophysiologic relevance feedback in intent modeling for information retrieval

Information Retrieval using Relevance Feedback

Neural Relevance Feedback for Information Retrieval

Relevance feedback is a technique used in interactive Information Retrieval (IR) systems to enable a user to provide additional information to help the system identify more relevant documents. The additional information is provided in the form of relevance judgements on retrieved documents. One of the most advanced relevance feedback technique in operative IR system is based on a probabilistic ...

User Relevance Feedback in Semantic Information Retrieval

The user dimension is a crucial component in the information retrieval process and for this reason it must be taken into account in planning and technique implementation in information retrieval systems. In this paper we present a technique based on relevance feedback to improve the accuracy in an ontology based information retrieval system. Our proposed method combines the semantic information...

Document 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...

Integrating Unlabeled Images for Image Retrieval Based on Relevance Feedback

Retrieval techniques based on pure similarity metrics are often suffered from the scales of image features. An alternative approach is to learn a mapping based on queries and relevance feedback by supervised learning. However, the learning is plagued by the insufficiency of labeled training images. Different from most current research in image retrieval, this paper investigates the possibility ...