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Meta Rank Search Engine: Enhancing Search Results through Page History Analysis

Explore innovative ranking methods using page history data from Amazon Alexa to improve search engine results from Google by re-ranking based on user preferences and historical insights. The project involves developing an interface for users to submit queries and using Google Search API and AWIS API for data retrieval.

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Meta Rank Search Engine: Enhancing Search Results through Page History Analysis

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  1. CSCI 572 Project Project Title: Deepin Search Member: Wenxu Li & ZimingZhai

  2. Project Description Reason: sometimes we want to get the latest web pages, and sometimes we want to get the most popular web pages. The search engine should give different ranks based on users’ requirement. History can tell us more about the web pages. A meta search engine that collaborates with page history. In this project, we will design several ranking methods based on the page history information from Amazon Alexa Web Information Services, such as publish time, traffic and so on. And then use our ranking methods to re-rank the results from google search engine.

  3. Implementation Strategy Design an interface that allows user to submit queries Google Search Result We will use Google search API (In “Special Resources”) to retrieve the top 30 results from Google Amazon Alexa Web Information Services Open an account in Amazon and purchase AWIS ($0.15 per 1000 requests) Use AWIS API to retrieve the history information for each result URL Develop our ranking methods based on these information We will use Java, AWIS API, Google search API and jQuery

  4. Expected Interface Google realtime

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