Automatically Mining Facets for Queries from Their Search Results

Abstract

The problem of finding query facets which are multiple groups of words or phrases that explain and summarize the content covered by a query. This project assume that the important aspects of a query are usually presented and repeated in the query’s top retrieved documents in the style of lists, and query facets can be mined out by aggregating these significant lists. This Project propose a systematic solution, which we refer to as QD Miner, to automatically mine query facets by extracting and grouping frequent lists from free text, HTML tags, and repeat regions within top search results. Experimental results show that a large number of lists do exist and useful query facets can be mined by QD Miner. The further analyze the problem of list duplication, and find better query facets can be mined by modeling fine-grained similarities between lists and penalizing the duplicated lists.

Existing System

In Existing System a common procedure for conducting reformulation is to generate some candidate queries first, then a scoring method is employed to assess these candidates. Currently, most of the existing methods are context based. They rely heavily on the context relation of terms in the history queries and cannot detect and maintain the semantic consistency of queries. graphical model also captures the term context in the history query by skip-bigram and n-gram language models. That project investigate a social tagging data resource Delicious bookmark to generate addition and substitution patterns that are employed as supplements to the patterns generated from query log data.

Proposed System

In propose scheme QD Miner techniques are used. Query facets are mined by QD Miner. It is possible by extracting and grouping frequent lists from free text, HTML tags, and top search results. Semi-supervised bootstrapping list extraction algorithms can be used to iteratively extract more lists from the top results. Website wrappers also used to extract high-quality lists from authoritative websites.

Architecture