In this paper, a detailed survey on different facet mining techniques, their advantages and disadvantages is carried out. Facets are any word or phrase which summarize an important aspect about the web query. Researchers proposed different efficient techniques which improves the user's web query search experiences magnificently. Users are happy when they find the relevant information to their query in the top results. The objectives of their research are: (1) To present automated solution to derive the query facets by analyzing the text query; (2) To create taxonomy of query refinement strategies for efficient results; and (3) To personalize search according to user interest. Keyword:Web crawling Indexing QD miner Copyright © 2017Institute of Advanced Engineering and Science.All rights reserved. Corresponding Author:Duhita Pawar, Departement of Computer Engineering, Savitribai Phule Pune University, Near Jagrut School, Ma Shakti Nagar,Warud Email: duhita.pawar24@gmail.com INTRODUCTIONThere are different ways to help users to better describe their query information need. Query reformulation and query recommendation (or query suggestion) are two popular ways out of them. The main goal of facets mining is different from query recommendation and reformulation. The goal of the facet mining is to summarize the knowledge and information contained in the query. A query facet is a collection of related and informative words which describes important aspects of the query. Here a facet item is typically a word. A Web query has multiple facets that summarize the information about the query from different perspectives. If the user enter 'watches' as query then different aspects of the query 'watches' are displayed as facets which includes gender categories, brands, styles, colors, etc. Facets are assigned weight in order to display the facets priority wise. Techniques used in various approach as seen in Table 1.