Relevance Feedback using Surface and Latent Information in Texts

Relevance Feedback using Latent Information

We present a novel relevance feedback (RF) method that uses not only the surface information in texts, but also the latent information contained therein. In the proposed method, we infer the latent topic distribution in user feedback and in each document in the search results using latent Dirichlet allocation, and then we modify the search results so that documents with a similar topic distribu...

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...

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...

Information Retrieval using Relevance Feedback

Information Retrieval System Using Latent Contextual Relevance

When the relevance feedback, which is one of the most popular information retrieval model, is used in an information retrieval system, a related word is extracted based on the first retrival result. Then these words are added into the original query, and retrieval is performed again using updated query. Generally, Using such query expansion technique, retrieval performance using the query expan...