EGG (Enhanced Guided Google) — A meta search engine for combinatorial keyword search

The World Wide Web has immense resources for all kind of people for their specific needs. Searching on the Web using search engines such as Google, Bing, Ask have become an extremely common way of locating information. Searches are factorized by using either term or keyword sequentially or through short sentences. The challenge for the user is to come up with a set of search terms/keywords/sentence which is neither too large (making the search too specific and resulting in many false negatives) nor too small (making the search too general and resulting in many false positives) to get the desired result. No matter, how the user specifies the search query, the results retrieved, organized and presented by the search engines are in terms of millions of linked pages of which many of them might not be useful to the user fully. In fact, the end user never knows which pages are exactly matching the query and which the pages are not, till one checks it individually by referring that page. Providing the accurate and precise result to the end users has become Holy Grail for the search engines like Google, Bing, Ask etc. This research proposes a meta-search engine called EGG that is intended to use power of the Google for more accurate and combinatorial search. This is achieved through simple manipulation and automation of Google functions that are accessible from EGG through the Google.